Model Calculations Research Articles

Modeling noise from large-scale data center equipment

Data centers present unique noise modeling challenges due to the scale of equipment needed to meet cooling and backup power demands. Three-dimensional environmental noise modeling software that is based on ISO 9613-2 "Attenuation of sound during propagation outdoors" offers a range of modeling techniques. While more detailed modeling techniques may offer more accuracy in the near field, they also increase model calculation run times. Additionally, manufacturer sound emissions data often more closely align with simplified modeling techniques. This evaluation reviews common data center noise sources, reviews the range of manufacturer noise emissions data typically available for such sources, and compares noise modeling techniques with reference to on-site observations.

The Design and Experimentation of a Differential Grain Moisture Detection Device for a Combined Harvester.

To conveniently implement the online detection of grain moisture in combined harvesters and the address the influence of the no-load measurement baseline, thereby enhancing detection accuracy and measurement continuity, this study developed a differential grain moisture detection device. For its convenient installation and integration on combined harvesters, a single-pole plate measurement element with a 1.6 mm thick epoxy resin coated with a 2-ounce copper film was designed, and a grain moisture detection device was constructed based on the STM32F103 microprocessor (STMicroelectronics International NV, Geneva, Switzerland). To enhance the device's interference resistance, a differential amplification measurement circuit integrated with high-frequency excitation was designed using a reference capacitance. To improve the resolution of the measurement circuit, Malab simulations were conducted at different excitation frequencies, ultimately selecting 30 kHz as the system's excitation signal frequency. To validate the effectiveness of the measurement circuit, validity tests were performed on the constructed sensor, which showed that the sensor's measurement voltage could effectively distinguish the moisture levels in grains, with a determination coefficient (R²) reaching 0.9978. To address the errors in moisture measurement caused by changes in grain temperature, an interaction experiment of the effect of moisture content and temperature on the measurement voltage was conducted using an integrated temperature sensor, resulting in the construction of a moisture content calculation model. Both the indoor static detection and field testing of the moisture detection device were conducted, indicating that the maximum average error in static measurements was 0.3%, with a maximum relative error of 0.47%, and the average relative error in field tests was ≤0.4%.

Validation and Parametric Study of a Soil–Structure Interaction Nonlinear Simplified Model

This paper established a numerical model for the structure system in a soil–structure interaction using MATLAB 23.2 and ANSYS 24.1 software and validated the effectiveness and accuracy of a simplified nonlinear calculation model for soil–structure interaction through the numerical simulation results. Meanwhile, a list of key parameters was identified according to their influence on the simplified model, including the free field area, site soil parameters, equivalent soil area, superstructure size and number of stories, and input seismic waves. On this basis, a series of parametric investigations were carried out with the validated simplified model, by varying the selected key parameters. The research findings demonstrated that the simplified calculation model exhibited excellent accuracy and efficiency, and was capable of reflecting the nonlinear response of the structural system. It is applicable to the field of dynamic response analysis of the superstructure, considering soil–structure interaction.

Fate of supernova progenitors in massive binary systems

ABSTRACT How massive stars end their lives depends on the core mass, core angular momentum, and hydrogen envelopes at death. However, these key physical facets of stellar evolution can be severely affected by binary interactions. In turn, the effectiveness of binary interactions itself varies greatly depending on the initial conditions of the binaries, making the situation much more complex. We investigate systematically how binary interactions influence core–collapse progenitors and their fates. Binary evolution simulations are performed to survey the parameter space of supernova progenitors in solar metallicity binary systems and to delineate major evolutionary paths. We first study fixed binary mass ratios ($q=M_2/M_1$ = 0.5, 0.7, and 0.9) to elucidate the impacts of initial mass and initial separation on the outcomes, treating separately Type Ibc supernova, Type II supernova, accretion-induced collapse (AIC), rapidly rotating supernova (Ibc-R), black hole formation, and long gamma ray burst (long GRB). We then conduct 12 binary population synthesis model calculations, varying the initial condition distributions and binary evolution parameters, to estimate various supernova fractions. We obtain a Milky Way supernova rate $R_{\rm SN} = (1.78$–$2.47) \times 10^{-2} \, {\rm yr}^{-1}$ which is consistent with observations. We find the rates of AIC, Ibc-R, and long GRB to be $\sim 1/100$ the rate of regular supernovae. Our estimated long GRB rates are higher than the observed long GRB rate and close to the low luminosity GRB rate, although care must be taken considering our models are computed with solar metallicity. Furthering binary modelling and improving the inputs one by one will enable more detailed studies of these and other transients associated with massive stars.

Microbial Organic Fertilizer Combined with Magnetically Treated Water Drip Irrigation Promoted the Stability of Desert Soil Aggregates and Improved the Yield and Quality of Jujubes.

In the southern Xinjiang region of China, developing efficient irrigation and fertilization strategies to enhance resource utilization and prevent desertification is of critical importance. This study focuses on jujubes in Xinjiang, China, and involves a three-year field experiment aimed at exploring the optimal application strategy of magnetically treated water combined with microbial organic fertilizer to provide scientific support for high-quality jujube production. The experiment included a control group (using only fresh water, denoted as CK) and combinations of magnetically treated water drip irrigation with varying amounts of microbial organic fertilizer: in 2021, treatments included M0 (only irrigating with magnetically treated water), M6 (0.6 t/ha), M12 (1.2 t/ha), M18 (1.8 t/ha), and M24 (2.4 t/ha); in 2022 and 2023, treatments included M0, M6 (0.6 t/ha), M12 (1.2 t/ha), M24 (2.4 t/ha), and M48 (4.8 t/ha). This study investigated the effects of magnetically treated water drip irrigation combined with microbial organic fertilizer on soil physical properties, hydraulic parameters, enzyme activity, aggregate stability, and jujube yield and quality. The application of microbial organic fertilizer significantly reduced the soil bulk density by 3.07% to 11.04% and increased soil porosity by 1.97% to 14.75%. Soil saturated hydraulic conductivity gradually decreased with the increasing amount of microbial organic fertilizer, with a reduction range of 5.95% to 13.69%, while the water-holding capacity significantly improved (from 0.217 cm3/cm3 to 0.264 cm3/cm3). Additionally, microbial organic fertilizer significantly enhanced the activities of urease, catalase, and sucrase in the soil and significantly increased the proportion of large soil aggregates. Jujube yield increased by 3.66% to 21.38%, and the quality significantly improved, as evidenced by the increase in soluble sugar and flavonoid content. The Gauss model calculation results recommended 3.09 t·hm2 as the optimal amount of microbial organic fertilizer for comprehensively improving jujube yield and quality. These findings indicate that magnetically treated water drip irrigation combined with high amounts of microbial organic fertilizer significantly improved soil physical properties, hydraulic parameters, enzyme activity, aggregate stability, and jujube yield and quality, providing scientific evidence for desert soil improvement and agricultural production.

Multi-Source Feature-Fusion Method for the Seismic Data of Cultural Relics Based on Deep Learning.

The museum system is exposed to a high risk of seismic hazards. However, it is difficult to carry out seismic hazard prevention to protect cultural relics in collections due to the lack of real data and diverse types of seismic hazards. To address this problem, we developed a deep-learning-based multi-source feature-fusion method to assess the data on seismic damage caused by collected cultural relics. Firstly, a multi-source data-processing strategy was developed according to the needs of seismic impact analysis of the cultural relics in the collection, and a seismic event-ontology model of cultural relics was constructed. Additionally, a seismic damage data-classification acquisition method and empirical calculation model were designed. Secondly, we proposed a deep learning-based multi-source feature-fusion matching method for cultural relics. By constructing a damage state assessment model of cultural relics using superpixel map convolutional fusion and an automatic data-matching model, the quality and processing efficiency of seismic damage data of the cultural relics in the collection were improved. Finally, we formed a dataset oriented to the seismic damage risk analysis of the cultural relics in the collection. The experimental results show that the accuracy of this method reaches 93.6%, and the accuracy of cultural relics label matching is as high as 82.6% compared with many kinds of earthquake damage state assessment models. This method can provide more accurate and efficient data support, along with a scientific basis for subsequent research on the impact analysis of seismic damage to cultural relics in collections.

Impact of Installation Deviations on the Dynamic Characteristics of the Shaft System for 1 Gigawatt Hydro-Generator Unit

The shaft system, transferring the kinetic energy of water flow into electrical energy, is the most critical component in hydropower plants. Installation deviations of the shaft system for a giant hydro-generator unit can have significant impacts on its dynamic characteristics and overall performance. In this investigation, a three-dimensional geometry of the shaft system of an operating hydro-generator unit prototype with a rated power of 1 GW is established. Then, the calculation model of the shaft system is generated accordingly with tetrahedral and hexahedral elements. By applying different boundary conditions, the finite-element method is used to analyze the influences of installation deviations, including shaft radial misalignment and angular misalignment, on the dynamic characteristics of the shaft system. The calculation results reveal that the installation deviations change the natural frequencies, critical speeds, and mode shapes of the shaft system to a certain degree. The natural frequencies of the backward precession motion with installation deviations are reduced by 23% and 38% for the rated speed and the maximum runaway speed. Furthermore, for the forward precession motion, they increased by 30% and 48%, respectively. The critical speeds for the shaft system with radial and angular deviations are 3.2% and 3% larger than the critical speed of the shaft system without any mounting deviations. The radial and angular installation deviations below the maximum permissible values will not result in the structural performance degradation of the 1 GW hydro-generator shaft system. The conclusion drawn in this research can be used as a valuable reference for installing other rotating machinery.

Doping dependence and multichannel mediators of superconductivity: calculations for a cuprate model

We study two aspects of the superconductivity in a cuprate model system, its doping dependence and the influence of competing pairing mediators. We first include electron–phonon interactions beyond Migdal’s approximation and solve self-consistently, as a function of doping and for an isotropic electron–phonon coupling, the full-bandwidth, anisotropic vertex-corrected Eliashberg equations under a non-interacting state approximation for the vertex correction. Our results show that such pairing interaction supports the experimentally observed dx2−y2 -wave symmetry of the superconducting gap, but only in a narrow doping interval of the hole-doped system. Depending on the coupling strength, we obtain realistic values for the gap magnitude and superconducting critical temperature Tc close to optimal doping, rendering the electron–phonon mechanism an important candidate for mediating superconductivity in this model system. Second, for a doping near optimal hole doping, we study multichannel superconductivity, by including both vertex-corrected electron–phonon interaction and spin and charge fluctuations as pairing mechanisms. We find that both mechanisms cooperate to support an unconventional d-wave symmetry of the order parameter, yet the electron–phonon interaction is mainly responsible for the Cooper pairing and high critical temperature Tc . Spin fluctuations are found to have a suppressing effect on the gap magnitude and critical temperature due to their repulsive interaction at small coupling wave vectors.

A framework to analyse the probability of accidental hull girder failure considering advanced corrosion degradation for risk-based ship design

Ship’s hull girder failure could result from maritime accident that can cause human life loss, environmental disaster, and major economic impacts. In risk-based ship design paradigm, accounting for rare phenomena (e.g. ship-ship collision or grounding) is important to provide safe and durable structure. In-service corrosion-induced hull degradation should be considered at the design stage, as it can significantly affect structural strength. The current study presents a novel framework to estimate the probability of ship hull girder failure, accounting for novel corrosion modelling techniques and accidental damage. The associated uncertainties are considered using statistical sampling from evidence-based distributions. A state-of-the-art deterministic model for ultimate strength calculation is applied using Monte Carlo simulation approach, resulting in the probability of hull failure through a reliability assessment. Wave and still-water bending moments are considered random variables. Two case studies of tanker ships with varying sizes are executed to show the applicability of the proposed framework. The results indicate that proper consideration of corrosion is of high importance, as ageing can significantly increase the probability of failure if accidental damage happens. Therefore, whereas future research and model refinement are discussed, the presented framework can serve for risk-based ship design tool and assess existing structures’ safety.

Tricyclic 1,4-Diphosphinines: Local vs. Global Aromaticity.

1D and 2D (Sigma only model) calculations were performed on recently established tricyclic 1,4-diphosphinines as well as related benzene and pyrazine derivatives. The study was extended to evaluate the effect of the fused rings on the overall aromatic properties with a special focus on functional groups such as carbenes. The effect of non-aromatic heterocycles on the local ring current of the central ring is small, while aromatic heterocycles (e. g. NHC, imidazolium) lead to a global aromaticity. A higher sulfur content of the adjacent five-membered rings reduces the central ring current. The comparison to related tricyclic benzene and pyrazine derivatives showed that the 1,4-diphosphinine systems resemble more closely the situation in the benzene derivatives than the pyrazines. The effect of charged systems was studied using bis(TTF)-fused 1,4-diphosphinines and, according to values, the neutral form doesn't possess significant aromaticity but the tetracation resembles the global aromatic situation observed for other heterocycles in this study.

Modeling and Strength Calculations of Parts Made Using 3D Printing Technology and Mounted in a Custom-Made Lower Limb Exoskeleton.

This study is focused on the application of 3D-printed elements and conventional elements to create a prototype of a custom-made exoskeleton for lower limb rehabilitation. The 3D-printed elements were produced by using Fused Deposition Modeling technology and acrylonitrile butadiene styrene (ABS) material. The scope of this work involved the design and construction of an exoskeleton, experimental testing of the ABS material and numerical research by using the finite element method. On the basis of the obtained results, it was possible to deduce whether the load-bearing 3D-printed elements can be used in the proposed mechanical construction. The work contains full data of the material models used in FEM modeling, taking into account the orthotropic properties of the ABS material. Various types of finite elements were used in the presented FE models. The work is a comprehensive combination of material testing issues with the possibility of implementing the obtained results in numerical strength models of machine parts.

Charge Transfer Mechanism in Guanine-Based Self-Assembled Monolayers on a Gold Surface.

In this work, we have theoretically determined the one-electron oxidation potentials and charge transfer mechanisms in complex systems based on a self-assembled monolayer of guanine molecules adsorbed on a gold surface through different organic linkers. Classical molecular dynamics simulations were carried out to sample the conformational space of both the neutral and the cationic species. Thus, the redox potentials were determined for the ensembles of geometries through multiscale quantum-mechanics/molecular-mechanics/continuum solvation model calculations in the framework of the Marcus theory and in combination with an additive scheme previously developed. In this context, conformational sampling, description of the environment, and effects caused by the linker have been considered. Applying this methodology, we unravel the phenomena of electric current transport by evaluating the different stages in which charge transfer could occur. The results revealed how the positive charge migrates from the organic layer to the gold surface. Specifically, the transport mechanism seems to take place mainly along a single ligand and driven with the help of the electrostatic interactions of the surrounding molecules. Aside, several self-assembled monolayers with different linkers have been analyzed to understand how the nature of that moiety can tune the redox properties and the efficiency of the transport. We have found that the conjugation between the guanine and the linker, at the same time conjugated to the gold surface, gives rise to a more efficient transport. In conclusion, the established computational protocol sheds light on the mechanism behind charge transport in electrochemical DNA-based biosensor nanodevices.

BMP4 regulates asymmetric Pkd2 distribution in mouse nodal immotile cilia and ciliary mechanosensing required for left-right determination.

Mouse nodal immotile cilia mechanically sense the bending direction for left-right (L-R) determination and activate the left-side-specific signaling cascade, leading to increased Nodal activity. Asymmetric distribution of Pkd2, a crucial channel for L-R determination, on immotile cilia has been reported recently. However, the causal relationship between the asymmetric Pkd2 distribution and direction-dependent flow sensing is not well understood. Furthermore, the underlying molecular mechanism directing this asymmetric Pkd2 distribution remains unclear. The effects of several recombinant proteins and inhibitors on the Pkd2 distribution were analyzed using super-resolution microscopy. Notably, bone morphogenetic protein 4 (BMP4) affected the Pkd2 distribution. Additionally, three-dimensional manipulation of nodal immotile cilia using optical tweezers revealed that excess BMP4 caused defects in the mechanosensing ability of the cilia. Experimental data together with model calculations suggest that BMP4 regulates the asymmetric distribution of Pkd2 in nodal immotile cilia, thereby affecting the ability of these cilia to sense the bending direction for L-R determination. This study, for the first time, provides insight into the relationship between the asymmetric protein distribution in cilia and their function.

Modeling the γ spectrum from d−t collisions

Motivated by possible industrial fusion applications of spectroscopy of the γ rays accompanying d−t collisions we develop the first model calculations of the minor branching ratio of the d+t reaction, d+t→α+n+γ. The model exploits the most relevant physics feature—spin conservation in electric dipole transitions—which leads to a peculiar mechanism of this reaction: γ emission via bremsstrahlung from an intermediate α−n state. We highlight that, as a consequence of the bremsstrahlung, the γ spectrum contains nonzero contributions at all energies, thus making inclusive dtγ cross section measurements sensitive to the low-energy cutoff of the detected γ events. Comparison of our predictions to existing d+t→α+n+γ measurements in accelerators, employing cutoffs of 13 and 14 MeV, and inertial confinement fusion facilities, with a low-limit cutoff of 0.4 to 10 MeV, suggests a possible contradiction between results from these two types of experiments. Our predictions agree well with accelerator measurements and corroborate the cutoff dependence observed in inertial confinement experiments. These predictions are sensitive to the wave function details inside the short-range area of the α−n interaction, with uncertainty comparable to that of available experimental data, but become model independent below 4–5 MeV. This part of the γ spectrum features a previously unexpected rise, which below 0.5 MeV surpasses the main 17-MeV γ peak in strength. The reactivity of the d+t→α+n+γ branch was found to be proportional to its cross section. It strongly depends on the d−t plasma temperature, which opens the possibility of not only total d+t reactivity measurements but also advanced plasma temperature diagnostics. Published by the American Physical Society 2024

BMP4 regulates asymmetric Pkd2 distribution in mouse nodal immotile cilia and ciliary mechanosensing required for left-right determination.

Mouse nodal immotile cilia mechanically sense the bending direction for left-right (L-R) determination and activate the left-side-specific signaling cascade, leading to increased Nodal activity. Asymmetric distribution of Pkd2, a crucial channel for L-R determination, on immotile cilia has been reported recently. However, the causal relationship between the asymmetric Pkd2 distribution and direction-dependent flow sensing is not well understood. Furthermore, the underlying molecular mechanism directing this asymmetric Pkd2 distribution remains unclear. The effects of several recombinant proteins and inhibitors on the Pkd2 distribution were analyzed using super-resolution microscopy. Notably, bone morphogenetic protein 4 (BMP4) affected the Pkd2 distribution. Additionally, three-dimensional manipulation of nodal immotile cilia using optical tweezers revealed that excess BMP4 caused defects in the mechanosensing ability of the cilia. Experimental data together with model calculations suggest that BMP4 regulates the asymmetric distribution of Pkd2 in nodal immotile cilia, thereby affecting the ability of these cilia to sense the bending direction for L-R determination. This study, for the first time, provides insight into the relationship between the asymmetric protein distribution in cilia and their function.

Charge Transfer Mechanism in Guanine-Based Self-Assembled Monolayers on a Gold Surface.

In this work, we have theoretically determined the one-electron oxidation potentials and charge transfer mechanisms in complex systems based on a self-assembled monolayer of guanine molecules adsorbed on a gold surface through different organic linkers. Classical molecular dynamics simulations were carried out to sample the conformational space of both the neutral and the cationic species. Thus, the redox potentials were determined for the ensembles of geometries through multiscale quantum-mechanics/molecular-mechanics/continuum solvation model calculations in the framework of the Marcus theory and in combination with an additive scheme previously developed. In this context, conformational sampling, description of the environment, and effects caused by the linker have been considered. Applying this methodology, we unravel the phenomena of electric current transport by evaluating the different stages in which charge transfer could occur. The results revealed how the positive charge migrates from the organic layer to the gold surface. Specifically, the transport mechanism seems to take place mainly along a single ligand and driven with the help of the electrostatic interactions of the surrounding molecules. Aside, several self-assembled monolayers with different linkers have been analyzed to understand how the nature of that moiety can tune the redox properties and the efficiency of the transport. We have found that the conjugation between the guanine and the linker, at the same time conjugated to the gold surface, gives rise to a more efficient transport. In conclusion, the established computational protocol sheds light on the mechanism behind charge transport in electrochemical DNA-based biosensor nanodevices.

Research on energy storage capacity optimization of rural household photovoltaic system considering energy storage sharing.

With the promotion of the photovoltaic (PV) industry throughout the county, the scale of rural household PV continues to expand. However, due to the randomness of PV power generation, large-scale household PV grid connection has a serious impact on the safe and stable operation of the distribution network. Based on this background, this paper considers three typical scenarios, including household PV without energy storage, household PV with distributed energy storage, and household PV with centralized energy storage. Then, a calculation model for PV local consumption rate and annual net cost under different scenarios is constructed. Combined with a natural village in Shandong Province, the PV local consumption rate and annual net cost under three scenarios are compared and analyzed, and the potential of energy storage sharing in reducing storage capacity and improving PV local consumption is explored. The results show that configuring energy storage for household PV can significantly improve the power self-balancing capability. When meeting the same PV local consumption, household PV centralized energy storage can achieve smaller energy storage configuration and lower cost compared to household PV distributed energy storage. Finally, suggestions are proposed to further promote the development of household PV energy storage system. The research results can provide reference for improving the local consumption of rural household PV and accelerating the application of household PV energy storage system.

Research on energy storage capacity optimization of rural household photovoltaic system considering energy storage sharing.

With the promotion of the photovoltaic (PV) industry throughout the county, the scale of rural household PV continues to expand. However, due to the randomness of PV power generation, large-scale household PV grid connection has a serious impact on the safe and stable operation of the distribution network. Based on this background, this paper considers three typical scenarios, including household PV without energy storage, household PV with distributed energy storage, and household PV with centralized energy storage. Then, a calculation model for PV local consumption rate and annual net cost under different scenarios is constructed. Combined with a natural village in Shandong Province, the PV local consumption rate and annual net cost under three scenarios are compared and analyzed, and the potential of energy storage sharing in reducing storage capacity and improving PV local consumption is explored. The results show that configuring energy storage for household PV can significantly improve the power self-balancing capability. When meeting the same PV local consumption, household PV centralized energy storage can achieve smaller energy storage configuration and lower cost compared to household PV distributed energy storage. Finally, suggestions are proposed to further promote the development of household PV energy storage system. The research results can provide reference for improving the local consumption of rural household PV and accelerating the application of household PV energy storage system.

Construction method of fault function test case for Primary-Secondary fusion switch in distribution network

Test case design is the key to effective quality inspection of electrical equipment. To tackle the challenges of inadequate scenario coverage and disparate difficulty levels in the detection of single-phase ground faults in power distribution primary and secondary fusion switch, we propose a case construction method utilizing Latin hypercube sampling (LHS) based on NSGA-II double-objective optimization. Initially, the method investigates the primary factors influencing waveform detection difficulty and determines their respective weights through measurement and calculation, thus establishing a comprehensive model for calculating difficulty coefficients. Then, based on the dual objectives of uniformity and difficulty balance, we introduce a double-objective optimization LHS generation algorithm to construct a multi-dimensional detection cases of single-phase ground fault in power distribution primary and secondary fusion switch. Finally, the difficulty coefficient calculation model and the constructed test case undergo validation using actual test results, demonstrating a 43.59% efficiency improvement on the premise of ensuring the detection efficacy.

Ecological Function Zoning Framework for Small Watershed Ecosystem Services Based on Multivariate Analysis from a Scale Perspective

A thorough comprehension of distribution features of ecosystem services (ESs) and the influencing mechanisms can offer scientific guidance for the ecosystem management of small watersheds. We analyzed the spatial distribution patterns, interrelationships, and service hotspots of ESs across pixel and administrative scales using a multi-level statistical analysis approach in the Ashi River Basin. Through the quantitative calculation of the InVEST model, the findings revealed a decrease in soil retention, water yield, total nitrogen and phosphorus export, carbon storage, and habitat quality, while an increase in food production was observed during the period from 1995 to 2015. Through the geographical detector, the spatial heterogeneity of most individual ESs was influenced by land use patterns. Through redundancy analysis, terrain factors had the highest contribution rate to the integral ESs. Socio-economic factors and climate factors also drove the ESs’ amount and spatial distribution. At the pixel scale and administrative scale, there were distinctions in the correlations between all ESs, reflected by the fact that the relationships between ESs at the administrative scale were generally weaker and no more significant than at the pixel scale. Based on the number and distribution of hotspots in ESs and the clustering results of influencing factors, the framework of ecosystem zoning was constructed. This basin was divided into three ecological zones, and the management policies were formulated according to the ecological environment. This study clarifies the internal and mutual connection between ESs and influencing factors across two scales, thus contributing to the advancement of management strategies for ecological conservation and socio-economic development within the context of small watersheds.