Simulation Analysis Research Articles

Numerical study on solar photovoltaic/thermal system with tesla valve

In recent years, photovoltaic/thermal (PV/T) systems have played a crucial role in reducing energy consumption and environmental degradation, nonetheless, the low energy conversion efficiency presents a considerable obstacle for PV/T systems. Therefore, improving heat conversion efficiency is essential to enhance energy efficiency. In this paper, the PV/T system with the Tesla valve is proposed to solve this problem. Firstly, the cooling effect is simulated and analyzed in the system with four different flow channel structures: semicircle, rectangle, triangle and Tesla valve. The results indicate that the system with the Tesla valve exhibits superior cooling performance. Subsequently, several factors including angle, valve number, valve type, and pipe diameter ratio for the Tesla valve are further studied through numerical and simulation analysis. The results reveal that Tesla valves demonstrate optimal cooling performance when possessing the following structural parameters: complete symmetry, more valves, a 30-degree angle and a pipe diameter ratio of 1. Finally, four different types of fluid are selected to explore the Tesla valve. The conclusion shows that nanofluids with high density, low specific heat, and high thermal conductivity also improve the cooling performance. Thus, the PV/T system with the Tesla valve exhibits good heat dissipation and energy storage efficiency, electrical efficiency can reach 16.32% and thermal efficiency reach 59.65%.

Confidence intervals for mean response times of a open queueing network: calibration approach

Response time is a key factor in the analysis of the different queueing network model properties. This study computes a series of response times using a data-based recurrence relation. The true average response time is determined using the sample averages from those response times. Several confidence intervals are created for the open queueing net- work model’s average response times using the calibration approach. Using a numerical simulation analysis, the accuracy of the various confidence intervals is evaluated. Journal of Statistical Research 2023, Vol 57, No.1-2, pp.69-79

Optimizing power systems and microgrids: A novel multi-objective model for energy hubs with innovative algorithmic optimization

This article delves into the dynamics of power system and microgrid planning, emphasizing the emerging significance of energy hubs. The study introduces a pioneering multi-objective model that integrates economic considerations and microgrid pollution mitigation. The focus is on renewable sources such as wind and solar, coupled with advanced energy storage systems like E-fuel. Sophisticated probabilistic modeling techniques address uncertainties in renewable resources, complemented by a demand-side management program for cost reduction during peak hours. Transforming into an optimization problem, an innovative algorithm inspired by African vulture foraging behaviors provides a distinctive approach to energy landscape optimization. In a comparative analysis with established models, this approach demonstrates proficiency in simulating market behavior and providing optimal strategies for profit maximization. In a simulation analysis of four scenarios, the impact of risk assessment, a novel electronic fuel storage market, and an innovative energy storage solution on operational costs and pollution emissions is scrutinized. Notably, the proposed method excels in Case 4, showcasing a significant reduction in both operational costs and emissions. Case 4 demonstrates a substantial reduction in operational costs to $1745.732 and pollutant releases to 10753.621 kg, outperforming existing models with lower operational costs and pollutant releases.

Large Eddy Simulation and Acoustic Analysis of Combustion Instability in an Annular Combustor with Low-Swirl Flames

Large Eddy Simulation and Acoustic Analysis of Combustion Instability in an Annular Combustor with Low-Swirl Flames

Preparation of (S)-epichlorohydrin using a novel halohydrin dehalogenase by selective conformation adjustment.

Chiral epichlorohydrin (ECH) is an attractive intermediate for chiral pharmaceuticals and chemicals preparation. The asymmetric synthesis of chiral ECH using 1,3-dicholoro-2-propanol (1,3-DCP) catalyzed by a haloalcohol dehalogenase (HHDH) was considered as a feasible approach. However, the reverse ring opening reaction caused low optical purity of chiral ECH, thus severely restricts the industrial application of HHDHs. In the present study, a novel selective conformation adjustment strategy was developed with an engineered HheCPS to regulate the kinetic parameters of the forward and reverse reactions, based on site saturation mutation and molecular simulation analysis. The HheCPS mutant E85P was constructed with a markable change in the conformation of (S)-ECH in the substrate pocket and a slight impact on the interaction between 1,3-DCP and the enzyme, which resulted in the kinetic deceleration of the reverse reactions. Compared with HheCPS, the catalytic efficiency (kcat(S)-ECH/Km(S)-ECH) of the reversed reaction dropped to 0.23-fold (from 0.13 to 0.03mM-1s-1), while the catalytic efficiency (kcat(1,3-DCP)/Km(1,3-DCP)) of the forward reaction only reduced from 0.83 to 0.71mM-1s-1. With 40mM 1,3-DCP as substrate, HheCPS E85P catalyzed the synthesis of (S)-ECH with the yield up to 55.35% and the e.e. increased from 92.54 to >99%. Our work provided an effective approach for understanding the stereoselective catalytic mechanism as well as the green manufacturing of chiral epoxides.

Numerical simulation and experimental study on the compression performance of a double layer cross-lattice-core sandwich structure

Lattice sandwich structures are widely used in many engineering fields for their excellent mechanical properties, such as aerospace, transportation, construction and so on. In this paper, a new type of double layer cross-lattice-core sandwich structure is proposed. Firstly, based on the nonlinear finite element software ABAQUS, a finite element numerical simulation analysis is processed to the sandwich structure unite cell under flat compression. The deflection pattern, load-displacement curve and internal energy-displacement curve are obtained to discuss the compression performance of the unite cell with some specific geometric parameters, such as arm length ratio, clamped angle and thickness of the cross-lattice-core. It is found that the compression performance of the lattice sandwich structure with an arm length ratio of 1 and an included angle of 90° is optimal. The energy absorption effect decreases slightly with the increases of the arm length ratio increases, which will be greatly reduced when the core angle is lower than 90°. Then the unite cell model of the structure is prepared using 3D printing technology, and its compression performance is investigated by flat compression tests and verified in comparison with the numerical analysis results. Finally, the load-bearing property of the structure is further verified by compression analysis of a plate structure consisting of several unite cells. The results provide a reference for the design and engineering application of the structure.

Decision Analysis of Cold Chain Supply Chain Based on a Stochastic Evolution Model

Accelerating the development of cold chain logistics for agricultural products is not only an objective requirement for the development of agricultural product circulation but also a necessary demand to promote rural revitalization and upgrade agricultural consumption. Addressing the evolutionary problems of cold chain transportation in uncertain environments, this study considers the actual stochastic disturbances in the cold chain supply chain system, introducing Gaussian white noise to reflect the random perturbations experienced during the evolution of the cold chain. A three-party stochastic evolutionary game model is established involving farmers, logistics enterprises, and government regulatory authorities. Based on this model, numerical simulation analysis is conducted to explore the effects of different factors such as the intensity of random disturbances and the loss transfer coefficient on the fluctuation of strategic choices of the entities and the convergence speed to a stable state during evolution. Finally, combining the results of numerical simulation, relevant policies and recommendations are proposed to provide insights and guidance for the development of cold chain logistics in agricultural products.

The power of Para sport: the effect of performance-focused swimming training on motor function in adolescents with cerebral palsy and high support needs (GMFCS IV) – a single-case experimental design with 30-month follow-up

ObjectiveThis study aims to evaluate the effect of a performance-focused swimming programme on motor function in previously untrained adolescents with cerebral palsy and high support needs (CPHSN) and to determine...

Does online high-volume hemodiafiltration offer greater efficiency and sustainability compared to high-flux hemodialysis? A detailed simulation analysis anchored in real-world data

Abstract Recent findings, including the CONVINCE study report, suggests the superiority of high-volume hemodiafiltration over high-flux hemodialysis in improving patients’ outcomes. Despite positive patient outcomes, concerns have arisen about the potential negative environmental impact of high-volume hemodiafiltration, as it may lead to increased water and dialysis fluid consumption and higher waste production. In this manuscript, we address the environmental impact of high-volume HDF, focusing on three key factors: water treatment consumption, dialysis fluid consumption, and solute efficiency markers of HD and HDF. By optimizing HDF prescription through adjustments in operational capabilities, such as reducing the QD/QB ratio to 1,2 rather than 1,5 and incorporating automated ultrafiltration and substitution control, it has been demonstrated that HDF delivers a higher dialysis dose for small and middle-molecule uremic compounds with the same dialysis fluid consumption and at equal dialysis doses dialysis fluid consumption is reduced. This finding is supported by real-world data from 26 031 patients who underwent high-volume postdilution hemodiafiltration at a reduced dialysis flow (550 ml/min) and achieved an effective OCMKt/V of 1.70. In addition, simulation modeling calculations, using blood extraction coefficient, dialysate saturation coefficient, and solute clearances with urea (small MW) and ß2M (middle MW), consistently show postdilution HDF's superiority to HD. This holds true even with a significant reduction in dialysis flow down to 440 ml/min reflecting QD/QB ratio of 1,2. Postdilution HDF generates high ultrafiltrate flow (up to 35% of blood flow), delivering saturated ultrafiltrate to the lower solute concentration containing effluent dialysate, thus enhancing solute clearance which opens the way to reduce the dialysis flow. In conclusion, our analysis, combining simulation and real-world data, suggests that postdilution HDF could be a more environmentally friendly treatment option compared to conventional hemodialysis. Additionally, automated user-friendly functions that minimize dialysis fluid use, can further strengthen this environmental benefit while enhancing efficiency.

Implementation of a Microgrid System with a Four-Phase Inductor Coupled Interleaved Boost Converter for EV Charging Stations

Electric vehicle charging stations are essential to enable broad reception due to the rise in electric vehicles in the transportation industry because they will lessen range anxiety concerns about distance. The primary objective of this work is to design a microgrid that is effective and affordable for an electric vehicle charging station that combines a photovoltaic, wind, and utility grid energy system (optional) as a principal source of energy. The proposed study employs a four-phase inductor coupled interleaved boost converter which is compact and effective with high power output which results in charging a vehicle within 33 min. A perturb and observe MPPT approach based on DC converters is used along with the digital 2PI controller to increase the effectiveness and performance of distributed energy systems. To make the converter a hassle-free operation, an interleaving technique is applied to the developed converter which results in ripple reduction, which results in an increase in the output current and voltage gain, with high power density and efficiency. For better understanding, real-time data for 2W/3W/4W are acquired and tested for various conditions and the maximum state of charge for the battery is gained within one-third of the usual time. At present, the interleaved converter’s operation is theoretically examined, and the behavior of the converter and the charging conditions of several electric vehicle systems are compared and shown in the simulation analysis.

Multi-condition simulation analysis of a sliding hydraulic support system based on elastoplastic mechanics

In response to the challenges of supporting fractured and weak surrounding rock in deep coal mines in the Huainan region of China, a self-moving hydraulic support system for roof support was designed and developed. This innovative solution addresses the difficulties encountered in providing continuous support to roof structures. Based on the theory of elastoplastic mechanics, a numerical analysis model was established to calculate the mechanical parameters such as the displacement, stress, and strain of hydraulic supports during the stepping process under multiple operating conditions. The results of the numerical simulation were compared and verified with those from an actual working site. The results show that the maximum equivalent stress is 245.33 MPa for operating condition 1, 246.82 MPa for operating condition 2, and 245.27 MPa for operating condition 3. The maximum stress values under the three working conditions do not exceed the yield strength of the material, satisfying the requirements for normal bracket support operations. These research findings can establish a theoretical framework for the comprehensive assessment of the reliability and stability of hydraulic supports and the optimization of construction processes.

Experimental and numerical investigation on the impact response of bolt-ball joints

The densely populated space lattice structure requires reliable performance under impact loads. The bolt-ball joint serves a crucial role in connecting members at various angles, significantly contributing to the overall safety of the structure. However, there is limited literature available on the impact resistance of the bolt-ball joint. In this study, the drop hammer impact test system was employed to conduct impact tests on 11 specimens of bolt-ball joints. Comprehensive records were maintained, including the final deformation states, video recordings of the impact process, and data on impact force, displacement, and strain. Additionally, numerical simulation analysis was conducted to expand the scope of the study. Five failure modes were observed: global bending deformation, bolt fracture, local denting, coupling deformation of local denting and global bending deformation, bolt and tube fracture. When the impact applied at the bolt ball or conical head and steel tube welding positions, the impact process was categorized into three stages: inertia, global bending deformation, and elastic recovery/bolt fracture. When the impact position was the steel tube, coupling deformation and elastic recovery/ bolt and tube fracture were observed. The energy absorption during the impact test was analyzed, revealing a positive correlation between the degree of specimen failure and the proportion of energy absorbed relative to the work done by the impact force. The effects of impact velocity, impact position, bolt dimension and impact angle on the dynamic response of the specimens were thoroughly analyzed.

Structure-Based Virtual Screening Identifying Novel FOXM1 Inhibitors as the Lead Compounds for Glioblastoma

Background: Glioblastoma multiforme (GBM) is a highly heterogeneous brain tumor with limited treatment options and a poor prognosis. Cancer stem cells (CSCs) have emerged as a critical factor in GBM resistance and management, contributing to tumor growth, heterogeneity, and immunosuppression. The transcription factor FOXM1 has been identified as a key player in the progression, spread, and therapy resistance of various cancers, including GBM. Objective: In this research, the objective was to perform structure-based in silico screening with the aim of identifying natural compounds proficient in targeting the DNA-binding domain (DBD) of the FOXM1 protein. Methods: In this study, in silico tools were employed for screening a hundred naturally occurring compounds capable of targeting the FOXM1 protein. Through molecular docking analysis and pharmacokinetic profiling, five compounds were found to be promising candidates for extensive interaction with the FOXM1 protein. Further, these compounds were validated for the stability of the FOXM1-natural compound complex using molecular dynamics (MD) simulations. Results: Four compounds, such as Withaferin A, Bryophyllin A, Silybin B, Sanguinarine and Troglitazone (control compound), emerged as promising candidates with substantial interactions with FOXM1, suggesting their potential as a protein inhibitor based on molecular docking investigations. After MD simulation analysis, the FOXM1- Bryophyllin A complex was found to maintain the highest stability, and the other three ligands had moderate but comparable binding affinities over a period of 100 ns. Conclusion: This study provides valuable insights into four promising FOXM1 inhibitors that have the ability to induce senescence in GBM stem cells. These findings contribute to the development of structure-based designing strategies for FOXM1 inhibitors and innovative therapeutic approaches for the treatment of Glioblastoma.

A Low-Frequency Fiber Bragg Grating Acceleration Sensor Based on Spring Support and Symmetric Compensation Structure with Flexible Hinges

To measure vibration signals, a low-frequency fiber Bragg grating (FBG) acceleration sensor featuring a flexible hinge with a spring support and symmetric compensation structure has been designed. Based on the mechanical model of the sensor’s structure, the expressions for sensitivity and resonant frequency of the sensor are derived. The structural parameters of the sensor are optimized, and a simulation analysis is conducted using ANSYS 19.2 software. According to the results of simulation analysis and size optimization, the sensor prototype is constructed. Subsequently, its amplitude-frequency response, sensitivity, and temperature characteristics are investigated through vibration experiments. The experimental results show that the resonant frequency of the sensor is 73 Hz, the operating frequency range is 0~60 Hz, and the sensitivity measures 24.24 pm/g. This design meets the requirements for measuring vibration signals at low frequencies.

Allosteric Regulation and Inhibition of Coronavirus 3CLpro Revealed by HDX-MS.

Coronavirus (CoV) infections have caused contagious and fatal respiratory diseases in humans worldwide. CoV 3-chymotrypsin-like proteases (3CLpro or Mpro) play an important role in viral maturation, and maintenance of their dimeric conformation is crucial for viral activity. Therefore, allosterically regulated dimerization of 3CLpro can be employed as a drug development target. Here, we investigated the allosteric regulatory mechanism of 3CLpro dimerization by using hydrogen/deuterium exchange coupled with mass spectrometry (HDX-MS) technology. We found that the FLAG tag directly coupled to the N-finger of 3CLpro significantly increased HDX kinetics at the dimer interface, and 3CLpro transformed from a dimer to a monomer. The 3CLpro mutants of SARS-CoV-2, which are monomeric, also exhibited increased deuterium exchange. Binding of the allosteric inhibitor Gastrodenol to most betacoronavirus 3CLpros led to increased allosteric deuterium exchange, resulting in the monomeric conformation of the CoV 3CLpro upon binding. Molecular dynamics (MD) simulation analysis further indicated the molecular mechanism of action of Gastrodenol on CoV 3CLpro: binding of Gastrodenol to SARS-CoV-2 3CLpro destroyed the hydrogen bond in the dimer interface. These results suggest that Gastrodenol may be a potential broad-spectrum anti-betacoronavirus drug.

An adaptive Morlet wavelet-based iterative filtering method for locating informative frequency band

Locating the informative frequency band of rolling bearing fault signals is of great significance for feature extraction and fault diagnosis. Benefiting from the adjustable center frequency and bandwidth as well as the similarity to impulse-like characteristics induced by bearing failures, Morlet wavelets are commonly used in resonance demodulation. However, fault impulses are highly susceptible to contamination by strong noise, which impedes the efficacy of existing wavelet parameter selection strategies and frequency band optimization methods. In this paper, an adaptive Morlet wavelet-based iterative filtering (AMIF) method is proposed for frequency band optimization under strong noise. The resonance frequency band is pinpointed based on adaptive Morlet wavelet filter banks, with off-band noise being canceled and fault features being refined during the level-by-level filtering process. Additional iterative operations are leveraged to enhance fault features of in-band signals to facilitate the optimization of the filtering parameters. Effectiveness of the proposed AMIF method and its superiority over the wavelet packet transform-based kurtogram and minimum entropy deconvolution are verified through simulation and experimental analysis. The results demonstrate that AMIF can accurately localize the informative frequency band, thereby extracting high-quality fault features, making it suitable for bearing fault diagnosis under strong noise condition with different fault types.

Reliability evaluation in the zero‐failure Weibull case based on double‐modified hierarchical Bayes

AbstractHierarchical Bayes, or E‐Bayes, is frequently used to estimate the failure probability when solving a zero‐failure reliability evaluation model; however, the accuracy of the reliability estimation using these methods is not very good in practice. Due to this, a novel double‐modified hierarchical Bayes (DMH‐Bayes) is proposed for Weibull characteristic data in this study to enhance failure probability estimation and improve reliability point estimation accuracy. Meanwhile, in order to guarantee the preservation of the assessment findings' consistency and confidence level, the parametric Bootstrap method (P‐Bootstrap) and the L‐moment estimation method based on point estimation are introduced to obtain reliability confidence interval estimates. Based on Monte–Carlo simulation testing and analysis of a gyroscope bearing, the new model is confirmed to have better applicability and robustness while improving the accuracy of reliability assessment.

Experimental measurement and molecular dynamics simulation analysis of thermal aging performance in composite solid propellants

As a complex mixed system, the aging mechanism of high-energy composite materials involves the aging of each component itself, interactions between components, and transformation of microstructural and thermodynamic properties. The study of a single component or performance parameter has great limitations for elaborating the cognitive complexity of aging processes, making it difficult to reveal the underlying principles of physicochemical property transformation. Thus, it can only be applied as an empirical summary. In view of this, this study comprehensively utilized numerical analysis and experimental detection to explore the evolution of micromolecular conformation and changes in macro aging performance from four aspects of composite systems, including binder aging, plasticizer migration, bond interface debonding, and mechanical property transformation. There was good consistency observed between molecular simulation and thermal aging experiments, indicating that there was basically no post curing process for HTPB propellants using TDI as the curing agent. In the early stage of aging, scission chain was the main process and, in the later stage of aging, oxidation crosslinking the main process. Oxidative crosslinking increased the mean square radius of gyration and glass transition temperature of the binder system, reduced the peak value of radial distribution function, and revealed the reason for the change of propellant hardness and CC and CO double bond content. However, chain degradation increased the number of polar groups, enhanced intermolecular polarity, reduced the solubility parameter, and increased the free volume fraction of the mixed system and the dioctyl sebacate diffusion coefficient. This resulted in an increase in the tangent value of the HTPB propellant loss angle from 0.43 to 0.44° and a decrease in the glass transition temperature from 203.3 to 202.0 K. The binding energy at the interfaces of AP/HTPB and Al/HTPB increased first and then decreased, which was consistent with SEM images of bonding interfaces. The joint effect of binding energy and mechanical properties of the binder system promoted the transformation of the stress-strain curve of aging propellant.

Multiscale Analysis of the Flexural Performance of FRP Reinforced Concrete Structures

Based on existing experimental data and analysis, seven different FRP bar models including Carbon Fiber Reinforced Polymer (CFRP), Basalt Fiber Reinforced Polymer (BFRP), Aramid Fiber Reinforced Polymer (AFRP), Glass Fiber Reinforced Polymer (GFRP), GFRP and CFRP combined (G-C), GFRP and AFRP combined (G-A), BFRP and CFRP combined (B-C), and BFRP and AFRP combined (B-A) were established. Finite element simulation analysis was conducted on seven different FRP bar combinations under static load bending tests. The flexural behavior of the specimens reinforced with different FRP bar combinations and their influencing factors were analyzed. The results showed that using AFRP as the reinforcement material for FRP composite bars in FRP reinforced concrete beams cannot effectively enhance the overall load-carrying capacity of the composite bars. The combination of CFRP with GFRP and BFRP bars significantly increases the stiffness of the FRP bar structure and improves the structural load-carrying capacity of the concrete beams.

The Impact of the Industrial Internet on the Innovation and Development Level of China’s Manufacturing Industry: Under the Perspective of Government Incentives

In the era of the digital economy, it has become an inevitable trend for manufacturing enterprises to establish industrial Internet platforms toward achieving transformation and innovative development. However, the current development model of industrial Internet platforms is still imperfect, wherein the application scenario is complex, the investment cost is too high, the return-on-investment cycle is too long, and other factors have hindered the willingness of manufacturing enterprises to employ cloud services and capital investment. For this reason, governments have introduced a series of relevant incentive policies to promote the development of industrial Internet platforms and the transformation and upgrading of manufacturing enterprises. Considering the role of government incentives, this study first constructs an evolutionary game model with local governments, manufacturing enterprises, and industrial Internet platforms as the main players. Then, the dynamic change process of each game player’s strategy choice and the stable state of the system evolution under multiple scenarios are analyzed, and the validity of the conclusions is verified through a numerical simulation analysis. Finally, the statistical data of 28 provinces in China from 2018 to 2020 are used to conduct an empirical test to explore the impact of the industrial Internet on the transformation and innovation development of the manufacturing industry and the role of government incentives. The results show that the development of the industrial Internet has a significant role in promoting the innovation and development of the manufacturing industry; government incentives can promote the innovation and development of the industrial Internet and manufacturing industry, but incentives should not be too generous; and the impact of developing the industrial Internet on the level of innovation input/output of the manufacturing industry shows obvious regional differences. This study takes the local government as an independent game participant into consideration, which enriches the research field of combining evolutionary game theory with the transformation and innovative development of the manufacturing industry. In addition, this study provides theoretical guidance and practical references for the government to formulate incentive policies to promote the development of industrial Internet platforms and for manufacturing enterprises to utilize these platforms to carry out innovation and perform upgrades.