Numerical Study of a Three-Dimensional Laminar Flow in a Rectangular Channel with a 180-Degree Sharp Turn

This study presents a numerical analysis of three-dimensional steady laminar flow in a rectangular channel with a 180-degree sharp turn. The Navier-Stokes equations are solved by using finite difference method for Re = 900. Three-dimensional streamlines and limiting streamlines on wall surface are used to analyze the three-dimensional flow characteristics. Topological theory is applied to limiting streamlines on inner walls of the channel and two-dimensional streamlines at several cross sections. It is also shown that the flow impinges on the end wall of turn and the secondary flow is induced by the curvature in the sharp turn.

Use of the epitaxial MTBs as a 1D gate(Lg=0.4 nm)for the construction of scaling down two-dimensional field-effect transistors

In recent years,there has been a significant increase in research focused on the growth of large-area single crystals.Rajan et al.[1]recently achieved the growth of large-area monolayers of transition-metal chalcogenides through assisted nucleation.The quality of molecular beam epitaxy(MBE)-grown two-dimensional(2D)materials can be greatly enhanced by using sacrificial species deposited simultaneously from an electron beam evaporator during the growth process.This technique notably boosts the nucleation rate of the target epitaxial layer,resulting in large,homogeneous monolayers with improved quasiparticle lifetimes and fostering the development of epitaxial van der Waals heterostructures.Additionally,micrometer-sized silver films have been formed at the air-water interface by directly depositing electrospray-generated silver ions onto an aqueous dispersion of reduced graphene oxide under ambient conditions[2].

Special Section on High-Dimensional Signal Processing

Massive amounts of data are acquired in modern and future information technology industries such as communication,radar,and remote sensing.The presence of large dimensionality and size in these data offers new opportunities to enhance the performance of signal processing in such applications and even motivate new ones.However,the curse of dimensionality is always a challenge when processing such high-dimensional signals.In practical tasks,high-dimensional signals need to be acquired,processed,and analyzed with high accuracy,robustness,and computational efficiency.This special section aims to address these challenges,where articles attempt to develop new theories and methods that are best suited to the high dimensional nature of the signals involved,and explore modern and emerging applications in this area.

Tuning synergy between nickel and iron in Ruddlesden-Popper perovskites through controllable crystal dimensionalities towards enhanced oxygenevolving activity and stability

Ni-Fe-based oxides are among the most promising catalysts developed to date for the bottleneck oxygen evolution reaction(OER)in water electrolysis.However,understanding and mastering the synergy of Ni and Fe remain challenging.Herein,we report that the synergy between Ni and Fe can be tailored by crystal dimensionality of Ni,Fe-contained Ruddlesden-Popper(RP)-type perovskites(La_(0.125)Sr_(0.875))n+1(Ni_(0.25)Fe_(0.75))nO3n+1(n=1,2,3),where the material with n=3 shows the best OER performance in alkaline media.Soft X-ray absorption spectroscopy spectra before and after OER reveal that the material with n=3 shows enhanced Ni/Fe-O covalency to boost the electron transfer as compared to those with n=1 and n=2.Further experimental investigations demonstrate that the Fe ion is the active site and the Ni ion is the stable site in this system,where such unique synergy reaches the optimum at n=3.Besides,as n increases,the proportion of unstable rock-salt layers accordingly decreases and the leaching of ions(especially Sr^(2+))into the electrolyte is suppressed,which induces a decrease in the leaching of active Fe ions,ultimately leading to enhanced stability.This work provides a new avenue for rational catalyst design through the dimensional strategy.

Modifications in aroma characteristics of'Merlot'dry red wines aged in American,French and Slovakian oak barrels with different toasting degrees

Aging in oak barrels is widely used in enology which could bring flavor changes and aromatic complexity to wines.In the present study,the aroma compounds were analyzed from the‘Merlot’dry red wines,which were fermented in two types of fermenters(stainless steel tank and rotated oak barrel)and aged in six types of oak barrels(three geographic origins×two toasting degrees)for different time(0,3,6 and 9 months,respectively).Results showed that 30 volatiles were associated with barrels and increased during oak aging.The fermenters could influence the intensities of the toast,leathery,smoky,fruity,floral and caramel aromas.The concentration of whisky lactone,eugenol,cis-isoeugenol,and the intensities of the toast and spicy aromas were highest in the wines aged in American oak and were lowest in the wines aged in French oak barrels.The concentrations of guaiacol,syringol,trans-isoeugenol,furfural alcohol,vanilla,cis-whisky lactone enabled the medium toasting barrels to be distinguished from the light toasting ones.The compounds originating from the barrels could be used to distinguish the types of different barrels,but the other general grape-derived and fermentation-derived volatiles could not.The fermenters,oak species and toasting degrees of the barrels all had significant effects on the aroma profiles of the aged‘Merlot’dry red wines,but the influence of the geographic origin was not obvious.

Research on Condenser Deterioration Evolution Trend Based on ANP-EWM Fusion Health Degree

This study presents a proposed method for assessing the condition and predicting the future status of condensers operating in seawater over an extended period.The aim is to address the problems of scaling and corrosion,which lead to increased loss of cold resources.The method involves utilising a set of multivariate feature parameters associated with the condenser as input for evaluation and trend prediction.This methodology offers a precise means of determining the optimal timing for condenser cleaning,with the ultimate goal of improving its overall performance.The proposed approach involves the integration of the analytic network process with subjective expert experience and the entropy weightmethod with objective big data analysis to develop a fusion health degreemodel.The mathematical model is constructed quantitatively using the improved Mahalanobis distance.Furthermore,a comprehensive prediction model is developed by integrating the improved Informer model and Markov error correction.This model takes into account the health status of the equipment and several influencing factors,includingmultivariate feature characteristics.This model facilitates the objective examination and prediction of the progression of equipment deterioration trends.The present study involves the computation and verification of the field time series data,which serves to demonstrate the accuracy of the condenser health-related models proposed in this research.These models effectively depict the real condition and temporal variations of the equipment,thus offering a valuable method for determining the precise cleaning time required for the condenser.

Modelling rapid non-destructive test using light weight deflectometer on granular soils across different degrees of saturation

This study introduces an advanced finite element model for the light weight deflectometer(LWD),which integrates contact mechanics with fully coupled models.By simulating LWD tests on granular soils at various saturation levels,the model accurately reflects the dependence of the LWD modulus on dry density,water content,and effective stress.This model addresses and overcomes the limitations of previous finite element models for this specific problem.Simultaneously,this research presents the first experimentally validated fully coupled contact impact model.Furthermore,the research provides a comparative assessment of elastoplastic and nonlinear elastic models and contrasts an enriched node-tosegment method(developed in this study)with the more precise mortar technique for contact mechanics.These comparisons reveal unique advantages and challenges for each method.Moreover,the study underscores the importance of careful application of the LWD modulus,emphasising the need for sophisticated tools to interpret soil behaviour accurately.

Health effects of fruit juices and beverages with varying degrees of processing

The degree of processing is rarely considered an independent factor in the health effects of fruit juices and beverages(FJBs)consumption.In fact,the consumption of ultra-processed foods has been shown to pose health risks.In this study,we first integrated 4 systems used to classify the degree of food processing and then classified FJBs into three major categories,low(minimal),moderate and high.Second,we compared the differences in attitudes towards FJBs in dietary guidelines.Third,we integrated the results of existing epidemiological surveys,randomized controlled trials,and animal experiments to explore the health risks associated with consuming FJBs.Deepening the processing of FJBs has been found to lead to an increased risk of diseases.Dietary pattern,nutrients,addition agents and consumer preferences may be influential factors.Finally,we investigated whether there were any changes in the health benefits of 100%fruit juices produced by different processing methods.In conclusion,minimally/moderately processed 100%fruit juices provide more health benefits than highly processed fruit beverages.The results support the need to consider the extent of FJBs processing in future studies to adjust official nutritional recommendations for beverage consumption.

Higher-dimensional Chen-Lee-Liu equation and asymmetric peakon soliton

Integrable systems play a crucial role in physics and mathematics.In particular,the traditional(1+1)-dimensional and(2+1)-dimensional integrable systems have received significant attention due to the rarity of integrable systems in higher dimensions.Recent studies have shown that abundant higher-dimensional integrable systems can be constructed from(1+1)-dimensional integrable systems by using a deformation algorithm.Here we establish a new(2+1)-dimensional Chen-Lee-Liu(C-L-L)equation using the deformation algorithm from the(1+1)-dimensional C-L-L equation.The new system is integrable with its Lax pair obtained by applying the deformation algorithm to that of the(1+1)-dimension.It is challenging to obtain the exact solutions for the new integrable system because the new system combines both the original C-L-L equation and its reciprocal transformation.The traveling wave solutions are derived in implicit function expression,and some asymmetry peakon solutions are found.

Wellbore Cleaning Degree and Hydraulic Extension in Shale Oil Horizontal Wells

The efficient development and exploitation of shale oil depends on long-distance horizontal wells. As the degreeof cleaning of the wellbore plays a key role in these processes, in this study, this problem is investigated experimentallyby focusing on the dimensionless cuttings bed height. A method is proposed to calculate the horizontalwellhydraulic extension taking into account the influence of the wellbore cleaning degree on the wellborepressure distribution and assess the effect of a variety of factors such as the bottom hole pressure, the circulatingpressure drop, the drilling pump performance and the formation properties. The analysis shows that the hydraulicextension of horizontal wells decreases with an increase in the cuttings bed height, and the higher the displacementof drilling fluid, the faster the hydraulic extension declines. The annular pressure drop of the horizontalsection increases with the increase of the cuttings bed height, resulting in a higher bottom-hole pressure. Severalarguments are provided to guide the safe drilling of shale oil horizontal wells and overcome the limits of currenttechnological approaches.

A novel box-counting method for quantitative fractal analysis of threedimensional pore characteristics in sandstone

Fractal theory offers a powerful tool for the precise description and quantification of the complex pore structures in reservoir rocks,crucial for understanding the storage and migration characteristics of media within these rocks.Faced with the challenge of calculating the three-dimensional fractal dimensions of rock porosity,this study proposes an innovative computational process that directly calculates the three-dimensional fractal dimensions from a geometric perspective.By employing a composite denoising approach that integrates Fourier transform(FT)and wavelet transform(WT),coupled with multimodal pore extraction techniques such as threshold segmentation,top-hat transformation,and membrane enhancement,we successfully crafted accurate digital rock models.The improved box-counting method was then applied to analyze the voxel data of these digital rocks,accurately calculating the fractal dimensions of the rock pore distribution.Further numerical simulations of permeability experiments were conducted to explore the physical correlations between the rock pore fractal dimensions,porosity,and absolute permeability.The results reveal that rocks with higher fractal dimensions exhibit more complex pore connectivity pathways and a wider,more uneven pore distribution,suggesting that the ideal rock samples should possess lower fractal dimensions and higher effective porosity rates to achieve optimal fluid transmission properties.The methodology and conclusions of this study provide new tools and insights for the quantitative analysis of complex pores in rocks and contribute to the exploration of the fractal transport properties of media within rocks.

Numerical Investigation of Thermal Behavior of CNC Machine Tool and Its Effects on Dimensional Accuracy of Machined Parts

The dimensional accuracy of machined parts is strongly influenced by the thermal behavior of machine tools (MT). Minimizing this influence represents a key objective for any modern manufacturing industry. Thermally induced positioning error compensation remains the most effective and practical method in this context. However, the efficiency of the compensation process depends on the quality of the model used to predict the thermal errors. The model should consistently reflect the relationships between temperature distribution in the MT structure and thermally induced positioning errors. A judicious choice of the number and location of temperature sensitive points to represent heat distribution is a key factor for robust thermal error modeling. Therefore, in this paper, the temperature sensitive points are selected following a structured thermomechanical analysis carried out to evaluate the effects of various temperature gradients on MT structure deformation intensity. The MT thermal behavior is first modeled using finite element method and validated by various experimentally measured temperature fields using temperature sensors and thermal imaging. MT Thermal behavior validation shows a maximum error of less than 10% when comparing the numerical estimations with the experimental results even under changing operation conditions. The numerical model is used through several series of simulations carried out using varied working condition to explore possible relationships between temperature distribution and thermal deformation characteristics to select the most appropriate temperature sensitive points that will be considered for building an empirical prediction model for thermal errors as function of MT thermal state. Validation tests achieved using an artificial neural network based simplified model confirmed the efficiency of the proposed temperature sensitive points allowing the prediction of the thermally induced errors with an accuracy greater than 90%.

A related degree-based frequent pattern mining algorithm for railway fault data

It is of great significance to improve the efficiency of railway production and operation by realizing the fault knowledge association through the efficient data mining algorithm.However,high utility quantitative frequent pattern mining algorithms in the field of data mining still suffer from the problems of low time-memory performance and are not easy to scale up.In the context of such needs,we propose a related degree-based frequent pattern mining algorithm,named Related High Utility Quantitative Item set Mining(RHUQI-Miner),to enable the effective mining of railway fault data.The algorithm constructs the item-related degree structure of fault data and gives a pruning optimization strategy to find frequent patterns with higher related degrees,reducing redundancy and invalid frequent patterns.Subsequently,it uses the fixed pattern length strategy to modify the utility information of the item in the mining process so that the algorithm can control the length of the output frequent pattern according to the actual data situation and further improve the performance and practicability of the algorithm.The experimental results on the real fault dataset show that RHUQI-Miner can effectively reduce the time and memory consumption in the mining process,thus providing data support for differentiated and precise maintenance strategies.

Triad-displaced ULAs configuration for non-circular sources with larger continuous virtual aperture and enhanced degrees of freedom

Non-uniform linear array(NULA)configurations are well renowned due to their structural ability for providing increased degrees of freedom(DOF)and wider array aperture than uniform linear arrays(ULAs).These characteristics play a significant role in improving the direction-of-arrival(DOA)estimation accuracy.However,most of the existing NULA geometries are primarily applicable to circular sources(CSs),while they limitedly improve the DOF and continuous virtual aperture for noncircular sources(NCSs).Toward this purpose,we present a triaddisplaced ULAs(Tdis-ULAs)configuration for NCS.The TdisULAs structure generally consists of three ULAs,which are appropriately placed.The proposed antenna array approach fully exploits the non-circular characteristics of the sources.Given the same number of elements,the Tdis-ULAs design achieves more DOF and larger hole-free co-array aperture than its sparse array competitors.Advantageously,the number of uniform DOF,optimal distribution of elements among the ULAs,and precise element positions are uniquely determined by the closed-form expressions.Moreover,the proposed array also produces a filled resulting co-array.Numerical simulations are conducted to show the performance advantages of the proposed Tdis-ULAs configuration over its counterpart designs.

DOA estimation of high-dimensional signals based on Krylov subspace and weighted l_(1)-norm

With the extensive application of large-scale array antennas,the increasing number of array elements leads to the increasing dimension of received signals,making it difficult to meet the real-time requirement of direction of arrival(DOA)estimation due to the computational complexity of algorithms.Traditional subspace algorithms require estimation of the covariance matrix,which has high computational complexity and is prone to producing spurious peaks.In order to reduce the computational complexity of DOA estimation algorithms and improve their estimation accuracy under large array elements,this paper proposes a DOA estimation method based on Krylov subspace and weighted l_(1)-norm.The method uses the multistage Wiener filter(MSWF)iteration to solve the basis of the Krylov subspace as an estimate of the signal subspace,further uses the measurement matrix to reduce the dimensionality of the signal subspace observation,constructs a weighted matrix,and combines the sparse reconstruction to establish a convex optimization function based on the residual sum of squares and weighted l_(1)-norm to solve the target DOA.Simulation results show that the proposed method has high resolution under large array conditions,effectively suppresses spurious peaks,reduces computational complexity,and has good robustness for low signal to noise ratio(SNR)environment.

Degree of Freedom Analysis for Holographic MIMO Based on a Mutual-Coupling-Compliant Channel Model

Degree of freedom(DOF)is a key indicator for spatial multiplexing layers of a wireless channel.Traditionally,the channel of a multiple-input multiple-output(MIMO)half-wavelength dipole array has a DOF that equals the antenna number.However,recent studies suggest that the DOF could be less than the antenna number when strong mutual coupling is considered.We utilize a mutual-coupling-compliant channel model to investigate the DOF of the holographic MIMO(HMIMO)channel and give a upper bound of the DOF with strong mutual coupling.Our numerical simulations demonstrate that a dense array can support more DOF per unit aperture as compared with a half-wavelength MIMO system.

3-Dimensional Kinematic Comparison of Arm Movements between an Individual with NGLY1 Deficiency and a Neurotypical Individual

NGLY1 Deficiency is an ultra-rare autosomal recessively inherited disorder. Characteristic symptoms include among others, developmental delays, movement disorders, liver function abnormalities, seizures, and problems with tear formation. Movements are hyperkinetic and may include dysmetric, choreo-athetoid, myoclonic and dystonic movement elements. To date, there have been no quantitative reports describing arm movements of individuals with NGLY1 Deficiency. This report provides quantitative information about a series of arm movements performed by an individual with NGLY1 Deficiency and an aged-matched neurotypical participant. Three categories of arm movements were tested: 1) open ended reaches without specific end point targets;2) goal-directed reaches that included grasping an object;3) picking up small objects from a table placed in front of the participants. Arm movement kinematics were obtained with a camera-based motion analysis system and “initiation” and “maintenance” phases were identified for each movement. The combination of the two phases was labeled as a “complete” movement. Three-dimensional analysis techniques were used to quantify the movements and included hand trajectory pathlength, joint motion area, as well as hand trajectory and joint jerk cost. These techniques were required to fully characterize the movements because the NGLY1 individual was unable to perform movements only in the primary plane of progression instead producing motion across all three planes of movement. The individual with NGLY1 Deficiency was unable to pick up objects from a table or effectively complete movements requiring crossing the midline. The successfully completed movements were analyzed using the above techniques and the results of the two participants were compared statistically. Almost all comparisons revealed significant differences between the two participants, with a notable exception of the 3D initiation area as a percentage of the complete movement. The statistical tests of these measures revealed no significant differences between the two participants, possibly suggesting a common underlying motor control strategy. The 3D techniques used in this report effectively characterized arm movements of an individual with NGLY1 deficiency and can be used to provide information to evaluate the effectiveness of genetic, pharmacological, or physical rehabilitation therapies.

Further Analysis of Machine Tool Dimensional Accuracy and Thermal Stability under Varying Floor Temperature

Machining is as old as humanity, and changes in temperature in both the machine’s internal and external environments can be of great concern as they affect the machine’s thermal stability and, thus, the machine’s dimensional accuracy. This paper is a continuation of our earlier work, which aimed to analyze the effect of the internal temperature of a machine tool as the machine is put into operation and vary the external temperature, the machine floor temperature. Some experiments are carried out under controlled conditions to study how machine tool components get heated up and how this heating up affects the machine’s accuracy due to thermally induced deviations. Additionally, another angle is added by varying the machine floor temperature. The parameters mentioned above are explored in line with the overall thermal stability of the machine tool and its dimensional accuracy. A Robodrill CNC machine tool is used. The CNC was first soaked with thermal energy by gradually raising the machine floor temperature to a certain level before putting the machine in operation. The machine was monitored, and analytical methods were deplored to evaluate thermal stability. Secondly, the machine was run idle for some time under raised floor temperature before it was put into operation. Data was also collected and analyzed. It is observed that machine thermal stability can be achieved in several ways depending on how the above parameters are joggled. This paper, in conclusion, reinforces the idea of machine tool warm-up process in conjunction with a carefully analyzed and established machine floor temperature variation for the approximation of the machine tool’s thermally stability to map the long-time behavior of the machine tool.

Study on creep deformation and energy development of underground surrounding rock under four‐dimensional support

There is an urgent need to develop optimal solutions for deformation control of deep high‐stress roadways,one of the critical problems in underground engineering.The previously proposed four‐dimensional support(hereinafter 4D support),as a new support technology,can set the roadway surrounding rock under three‐dimensional pressure in the new balanced structure,and prevent instability of surrounding rock in underground engineering.However,the influence of roadway depth and creep deformation on the surrounding rock supported by 4D support is still unknown.This study investigated the influence of roadway depth and creep deformation time on the instability of surrounding rock by analyzing the energy development.The elastic strain energy was analyzed using the program redeveloped in FLAC3D.The numerical simulation results indicate that the combined support mode of 4D roof supports and conventional side supports is highly applicable to the stability control of surrounding rock with a roadway depth exceeding 520 m.With the increase of roadway depth,4D support can effectively restrain the area and depth of plastic deformation in the surrounding rock.Further,4D support limits the accumulation range and rate of elastic strain energy as the creep deformation time increases.4D support can effectively reduce the plastic deformation of roadway surrounding rock and maintain the stability for a long deformation period of 6 months.As confirmed by in situ monitoring results,4D support is more effective for the long‐term stability control of surrounding rock than conventional support.

A Dimensional Reduction Approach Based on Essential Constraints in Linear Programming

This paper presents a new dimension reduction strategy for medium and large-scale linear programming problems. The proposed method uses a subset of the original constraints and combines two algorithms: the weighted average and the cosine simplex algorithm. The first approach identifies binding constraints by using the weighted average of each constraint, whereas the second algorithm is based on the cosine similarity between the vector of the objective function and the constraints. These two approaches are complementary, and when used together, they locate the essential subset of initial constraints required for solving medium and large-scale linear programming problems. After reducing the dimension of the linear programming problem using the subset of the essential constraints, the solution method can be chosen from any suitable method for linear programming. The proposed approach was applied to a set of well-known benchmarks as well as more than 2000 random medium and large-scale linear programming problems. The results are promising, indicating that the new approach contributes to the reduction of both the size of the problems and the total number of iterations required. A tree-based classification model also confirmed the need for combining the two approaches. A detailed numerical example, the general numerical results, and the statistical analysis for the decision tree procedure are presented.