Multi-peak Distribution Research Articles

A data-driven robust optimization method based on scenario clustering for PVC production scheduling under uncertainty

In this paper, a data-driven robust optimization method based on scenario clustering is proposed for addressing energy consumption uncertainty characterized by correlation and multi-peaked distribution within the PVC production process. Firstly, principal component analysis (PCA) and kernel density estimation (KDE) methods are used to capture the correlation and distribution information effectively across multidimensional uncertain parameters; then a modified K-means clustering method based on density peaks is applied to cluster energy consumption scenarios and the flexible uncertainty subsets is established. A two-stage robust optimization model for the vinyl chloride production section is then proposed, and the column and constraint generation algorithm is applied to solved. Finally, the effectiveness of the proposed method is validated through a PVC production case study. Comparative results demonstrate that the proposed model reduces energy consumption under uncertainty and improves the robustness of PVC production scheduling.

Analysis of impact pressure, rock-breaking effect, and ground vibration induced by the disposable CO2 fracturing tube

The technology of expansion fracturing with liquid CO2 (EFLCO2) has attracted increasing attention due to reduced vibration and damage. The disposable fracturing tube has been developed and is gradually replacing the Cardox tube. However, there is a lack of impact pressure testing of disposable tubes under real working conditions, selection of gas explosion design parameters, and systematic analysis of blasting vibration. This limitation has constrained the widespread application of disposable fracturing tubes in engineering. A joint monitoring of the pressure-time curves in the disposable tubes and boreholes was conducted. The rock-breaking effect of varying hole spacing parameters in the EFLCO2 design was analyzed, and a systematic study was carried out on the vibration peak value, frequency, and energy characteristics. The results show that (1) the pressure distribution characteristics, stress peak value, and duration in the disposable tubes are different from those of Cardox tubes, which show multi-peak distribution, low-pressure peak value, and short duration. The correlation between the pressure in the disposable tube, filling pressure, and liquid CO2 weight is established, and a theoretical calculation method for the borehole wall pressure is proposed; (2) The hole spacing in rocks of different hardness is suggested; and (3) At the same scale distance, the peak particle velocity (PPV) caused by EFLCO2 (PPVCO2) is significantly smaller than that caused by blasting (PPVexplosive). The ratio of PPVexplosive to PPVCO2 is a power function related to scale distance, and a distance-related zonality exist in this relationship. The frequency composition of the vibration signal caused by EFLCO2 is relatively simple with a narrow frequency band. Its PPV and energy are mainly concentrated in the low-frequency band. This research contributes to the optimization of disposable fracturing tubes, gas explosion design, and vibration hazard control.

Experiments on heat transfer and film cooling characteristics of double-wall cooling structure with novel slot holes and pin-fins

The influences of blowing ratio, mainstream velocity, density ratio and jet Reynolds number on the heat transfer and film cooling properties of double-wall cooling cell (DWCC) with slot holes, impingement and diamond-shaped pin-fins were studied by means of pressure sensitive paint and transient liquid crystal. The simulation obtained the flow characteristic at a jet Reynolds number of 20000. The results indicated that with the increase of blowing ratio, the film cooling performance of DWCC structure also increased, and there was no film lift-off phenomenon which occurred in the cylindrical hole. The presence of pin-fins created a spike-shaped film in the slot outlet. Therefore, when studying the DWCC structure, it was important to consider the couple effects of impingement, pin-fins, and slot hole. As the density ratio decreased and the mainstream velocity increased, the film cooling effectiveness (FCE) gradually decreased. When jet Reynolds number increased from 20,000 to 60,000 under a density ratio of 2.0, the area-averaged FCE increased from 0.308 to 0.435, with an increase of up to 41.2%. The convective heat transfer level of impingement stagnation point was much higher than that of pin-fins region. Due to the transition between the impinging jet and the wall jet, the heat transfer coefficient (HTC) had a multi-peak distribution. In addition, several low heat transfer zones similar to wing-shaped, eye-shaped, and crescent-shaped were observed on the target surface and bottom surface inside the cooling cell. The DWCC structure studied in this paper is more efficient in cooling performance compared to traditional cooling structures. This makes it suitable for use in various fields such as heat transfer of turbine blades and electrical equipment.

A novel method for studying the wind speed probability distribution and estimating the average wind energy density

Traditional distribution models generally have large fitting errors at low wind speeds and poor fitting effects at multi-peak wind speed distributions. In this paper, a novel approach is proposed to fit different wind speed distributions, introducing a Gumbel distribution into common hybrid distribution models. The model parameters are solved by a combination of snake optimizer and nonlinear least squares (SO-NLS), using the optimal values obtained by the nonlinear least squares method as a set of initial input vectors for the snake optimizer. Simulation experiments were conducted using multi-peak wind speed distribution datasets with varying characteristics, comparing the fitting performance of the improved hybrid models against the conventional Weibull, Normal, and Rayleigh hybrid models. The results show that the proposed approach improved the model fit effects, particularly at low wind speeds, in all five experimental datasets. In most cases, the overall fitting effects were also improved. Furthermore, the validity and superiority of the improved hybrid models were further verified by comparing the estimated average wind energy density. Meanwhile, the experimental results also verified that SO-NLS not only yielded better optimization results but also accelerated the convergence speed than the snake optimizer. The improvements presented in this study effectively address the problem of large fitting errors at the low wind speed sections of the distribution, providing a theoretical basis for wind farm planning and design.

Multi-Source energy optimization method for supersonic aircraft based on multi-objective adaptive covariance matrix and chaotic search group algorithm

In the trend of increasing aircraft electrical power levels, future supersonic aircraft will have an urgent need for multi-source, adaptive, and high-energy-efficient approach to electrical power generation. In this paper, a multi-source energy optimization method based on multi-objective optimization algorithm MOACCGA is proposed. The method considers fuel consumption rate and thrust as the objective functions, with engine safety as a constraint. Based on the establishment of a small bypass ratio turbofan engine with multi-source energy extraction system, the influence mechanism of energy extraction on engine performance is analyzed. It is concluded that the generation of multi-source energy is optimizable, and the objective function has strong nonlinear and multi-peak distribution in the solution space. Then, the multi-objective adaptive covariance matrix and chaotic search group algorithm (MOACCGA) is proposed to solve the multi-source energy optimization problem. The algorithm utilizes the evolutionary approach with an adaptive covariance matrix to adapt to the strong nonlinearity of the system. Additionally, it overcomes the problem of getting trapped in local optima within the solution space characterized by multiple peak distributions by employing chaotic search. Finally, the multi-source energy optimization method is validated through simulations. In each condition, multi-source energy optimization can save fuel consumption by 0.7% of the total fuel consumption and reduce thrust loss by 1.5% of the total thrust.

Reliability model for key components of urban rail transit train based on improved hunter-prey optimization

The reliability of key components of urban rail transit (URT) plays an important role in the maintenance plans of URT. It is necessary to establish the reliability model of URT trains. In the current research, the reliability model has a limited scope of application and fails to accurately depict the reliability of key components in URT trains. To solve the above problem, a multi-peak type mixture Weibull distribution model is established using several three-parameter Weibull distributions based on fault modes of components sourced from historical lifetime data. Due to the complexity of this model, parameter estimation is challenging. For this purpose, an improved hunter-prey optimization (IHPO) was proposed to improve parameter estimation accuracy. Firstly, an improved Hénon chaos map was introduced to improve the distribution of the initial population. Secondly, the Lévy flight was introduced to increase the probability of the individual spreading to the whole range at the late stage. Lastly, a nonlinear balance factor was proposed to enhance the algorithm’s global search capability. The simulation experiment was carried out with examples of the balanced pressing wheel and the wheelset. The IHPO algorithm-based parameter estimation method shows the highest R-square with values of 0.996 and 0.999, respectively, and the lowest root mean square error with values of 0.019 and 0.008, respectively. The simulation results demonstrate that the stability and optimization of the HPO are improved, and the multi-peak mixture Weibull distribution model based on the IHPO can accurately depict URT trains’ reliability.

Full-Scale Pore Structure Characterization and Its Impact on Methane Adsorption Capacity and Seepage Capability: Differences between Shallow and Deep Coal from the Tiefa Basin in Northeastern China

Deep low-rank coalbed methane (CBM) resources are numerous and widely distributed in China, although their exploration remains in its infancy. In this work, gas adsorption (N2/CO2), mercury intrusion porosimetry, and 3D CT reconstruction were performed on five coal samples of deep and shallow low-rank coal from northeast China to analyze their pore structure. The impact of the features in the pore structure at full scale on the capacity for methane adsorption and seepage is discussed. The results indicate that there are significant differences between deep low-rank coal and shallow low-rank coal in terms of porosity, permeability, composition, and adsorption capacity. The full-scale pore distribution was dispersed over a broad range and exhibited a multi-peak distribution, with the majority of the peak concentrations occurring between 0.45–0.7 nm and 3–4 nm. Mesopores are prevalent in shallow coal rock, whereas micropores are the most numerous in deep coal rock. The primary contributors to the specific surface area of both deep and superficial coal rock are micropores. Three-dimensional CT reconstruction can characterize pores with pore size greater than 1 μm, while the dominating equivalent pore diameters (Deq) range from 1 to 10 μm. More mini-scale pores and fissures are observed in deep coal rock, while shallow coal rock processes greater total and connection porosity. Multifractal features are prevalent in the fractal qualities of all the numbered samples. An enhancement in pore structure heterogeneity occurs with increasing pore size. The pore structure of deep coal rock is more heterogeneous. Furthermore, methane adsorption capacity is favorably connected with D1 (0.4 nm < pore diameter ≤ 2 nm), D2 (2 nm < pore diameter ≤ 5 nm), micropore volume, and specific surface area and negatively correlated with D3 (5 nm < pore diameter ≤ 50 nm), showing that methane adsorption capability is primarily controlled by micropores and mesopores. Methane seepage capacity is favorably connected with the pore volume and connected porosity of macropores and negatively correlated with D4 (pore diameter > 50 nm), indicating that the macropores are the primary factor influencing methane seepage capacity.

Self-directed learning in post-graduate medical education: Self-judgement and supervisor judgement of competence development in Austrian nine-month basic training.

Self-directed learning in the workplace should lead to the mastery of predefined learning objectives, with subjective competence judgements steering learning and promoting acceptance of feedback. Rotations should support self-directed learning in basic training by allowing junior physicians (JPs) to apply basic clinical competencies in various internal medicine and surgical departments. The study hypothesises that rotations support self-directed learning, as measured by self-judgements and supervisor judgements. Additionally, it describes JPs' willingness to reflect on their learning needs at the end of their basic training. This longitudinal study comprises 147 pseudonymised logbooks completed by JPs from three Vienna healthcare group (WIGEV) clinics. The logbook accompanies JPs' training, requiring them and their supervising specialist physicians to rate their training goal completion (10-level % scale) in training months 2, 3, 5, 6, 8 and 9. In addition, in months 3, 6 and 9, the JPs document the level of competence (knowledge, experience and proficiency) they feel they have achieved for each learning objective specified by the Austrian medical association (ÖÄK). The self-judged level of training goal completion demonstrates a multi-peaked distribution with an increasing trend; the supervisors' judgement of JPs' level of training goal completion is almost parallel. The share of learning objectives where the required level of competence is seen as not yet mastered decreases throughout the training. In the 9th month of training, approximately ¼ of the JPs indicated a need to learn in ≥10% of the learning objectives, independent of the training clinic. After switching departments, JPs downgraded their rating of training goal completion. Rotation supports realistic self-judgement, as competencies must be applied and reassessed in a new context. Most JPs consider the required level of competence per learning objective to be mastered at the end of basic training, yet they remain prepared to reflect critically on their learning needs.

Probing the strongly correlated magnetic state of Co2C nanoparticles at low temperatures using μSR

Co2C nanoparticles (NPs) are amongst transition metal carbides whose magnetic properties have not been well explored. An earlier study (Roy et al 2021 J. Phys.: Condens. Matter 33 375804) showed that a pellet made from Co2C NPs exhibits exchange bias (EB) effect below a temperature, T EB = 50 K and a spin glass (SG) feature emerges below T SG = 5 K. In the current study we use magnetic, electrical transport, specific heat, and muon spin rotation (μSR) measurements to explore further the magnetic properties of a pellet made with 40 nm diameter pure Co2C NPs. We uncover the onset of Kondo localization at Kondo temperature T K (= 40.1 K), which is close to the onset temperature (T EB) of the EB effect. A crossover from the Kondo-screened scenario to the Ruderman–Kittel–Kasuya–Yosida interaction-dominated regime is also observed for T < T K. Temperature-dependent specific heat measurement further supports the Kondo localization scenario in the pellet and shows the heavy fermionic nature of the strongly correlated electronic state in Co2C. The zero field μSR asymmetry spectra in the low-temperature regime are characterized by two distinct fast and slow relaxation rates. The spectra show the absence of long-range magnetic order in the sample. However, our analysis suggests the NPs-pellet shows the presence of a dominant magnetically disordered fraction and a smaller fraction with short-range order. Muons in the disordered fraction exhibit a slower relaxation rate, while muons in the smaller fraction with short-range order exhibit a faster relaxation rate. We observe an increase in this fast relaxation rate between T EB and T SG. This increase below T EB ∼ 50 K suggests a slowing down of the fluctuating local magnetic environment around muons. Transverse field-μSR asymmetry spectra show the emergence of a stable, multi-peaked local magnetic field distribution in the pellet below T EB. Longitudinal field μSR spectra shows distinct changes in the dynamics of fluctuations suggesting the presence of a frozen glassy like state below 6 K. Based on our results, we suggest that below T EB, the pellet of Co2C NPs develops a magnetic interface that separates the two magnetic fractions; one is a disordered fraction, and the other is a fraction with short-range order. The exchange interaction that sets in below T EB at the interface couples the two fractions, leading to a suppression of the fluctuations. With the suppression of magnetic fluctuations below T EB, strong correlation effects in the electronic state of Co2C lead to Kondo localization.

Variance-aware spatial decoupling attention for stereo matching

The stereo matching algorithms which are based on feature matching build cost volume to regression disparity. Such cost volume shows a regular data distribution along the disparity dimension. The pixels with proper matching should have a single-peak distribution, while the pixels in the ill-conditioned regions have a multi-peak distribution. Using the variance of disparity dimension data, ill-conditioned regions can be identified. In this paper, an attention mechanism based on variance features is proposed, which promotes the neural network to deal with complicated regions. By decoupling the space of the image, a linear complexity attention mechanism is realized. It can be embedded into the algorithm based on feature matching with a slight increase in inference time, and a suitable trade-off is achieved in precision and speed. By embedding the module into BGNet, the accuracy of the designed model has been improved by 10 %, meanwhile, competitive performance has been achieved.

Credible Gaussian sum cubature Kalman filter based on non-Gaussian characteristic analysis

Toward the pose estimation problem of unmanned aerial vehicles (UAVs) flight over water, a credible Gaussian-sum cubature Kalman filter (CGSCKF) based on non-Gaussian characteristic analysis for nonlinear non-Gaussian system is proposed. In the framework of the proposed scheme, a data characteristic analysis based on multi-peak distribution degree, skewness and kurtosis is applied to evaluate the non-Gaussian intensity of noise, and a Gaussian mixture reduction (GMR) method based on the improved monarch butterfly optimization (IMBO) is proposed to improve the filtering accuracy in the case of weak non-Gaussian noise (Gaussian-like noise). In addition, considering the problem of inconsistency between the practical and the theoretic system model, the process noise and measurement noise are estimated online, and the credibility of filtering result, which is obtained by Gaussian-sum cubature Kalman filter (GSCKF), is measured by comparing the filtering error covariance with the true error covariance. Some comparison simulations and experiments with classical algorithms are provided, justifying that the proposed scheme has better performance in the pose estimation of UAV.

Deconvolution without calibration measurement of multi-peak charge distributions in dielectric materials

The electrical and mechanical properties of a dielectric material are significantly influenced by its charge distribution, necessitating an understanding of how charge accumulation occurs in order to determine the suitability of use for specific applications. This research presents a novel approach to deconvolving charge distributions with multiple peaks while dispensing with calibration measurement required by the non-contact pulsed electro-acoustic technique. Unlike traditional deconvolution methods that rely on reference signal measurements, the proposed approach reconstructs the charge distribution through parameters directly estimated from the piezoelectric transducer output voltage, effectively eliminating the need for such measurements altogether. Simulations show that even when closely spaced peaks exist within multi-peak charge distributions, our method can accurately reconstruct their profiles. In addition, the charge distributions obtained from experimental data of PTFE, FEP, and PEEK indicate that the proposed approach outperforms traditional methods in predicting penetration depth while reducing fluctuations and spurious peaks. We expect this method to be a valuable tool for the design and optimization of electronic systems in harsh environments through offering a simple, fast, and accurate alternative to conventional deconvolution methods.

On the Variability of a Simple Sensorimotor Reaction

To date, a wide variety of distributions of the simple sensorimotor reaction (SSR) has been studied. In this work, we also studied the distributions of this phenomenon, taking into account the fact that SSR has a constant and a variable part. The distribution of the constant component of the SSR had a normal character, while the distribution of the variable components had a more complex form. Analysis of the distribution of SSR in one subject for 36 minutes showed that both the constant and variable parts of SSR had a multi-peak distribution and a long “tail” in the range of large values. The study of the behavior of the SSR parameters over a relatively long period of time, along with an increase in the constant part of the SSR, revealed periodic and abrupt changes in both the constant component and the variable components. It is assumed that such differences are associated with a change in the structure of the transmission of excitation from sensors to the motor cortex over time.

Theory of space-time supermodes in planar multimode waveguides.

When an optical pulse is focused into a multimode waveguide or fiber, the energy is divided among the available guided modes. Consequently, the initially localized intensity spreads transversely, the spatial profile undergoes rapid variations with axial propagation, and the pulse disperses temporally. Space-time (ST) supermodes are pulsed guided field configurations that propagate invariantly in multimode waveguides by assigning each mode to a prescribed wavelength. ST supermodes can be thus viewed as spectrally discrete, guided-wave counterparts of the recently demonstrated propagation-invariant ST wave packets in free space. The group velocity of an ST supermode is tunable independently-in principle-of the waveguide structure, group-velocity dispersion is eliminated or dramatically curtailed, and the time-averaged intensity profile is axially invariant along the waveguide in absence of mode-coupling. We establish here a theoretical framework for studying ST supermodes in planar waveguides. Modal engineering allows sculpting this axially invariant transverse intensity profile from an on-axis peak or dip (dark beam) to a multi-peak or flat distribution. Moreover, ST supermodes can be synthesized using spectrally incoherent light, thus paving the way to potential applications in optical beam delivery for lighting applications.

Characterization method of core pore structure based on truncated Gaussian and its application in shale cores

The core pore structure is mainly described by fractal theory. Conventional single fractal models cannot express the multi-peak distribution characteristics of coal rock, shale, carbonate rock, and other cores. A multifractal model has numerous dimensions and discontinuous functions, making the model parameter selection difficult. Based on the capillary bundle theory and the truncated Gaussian distribution model, a model for characterizing the multi-peak distribution structure of cores is developed in this study. The model's accuracy is verified using the tested NMR experimental data of shale bimodal distribution and the cited coal trimodal distribution. This study further analyzes the influence of tortuosity and tortuosity fractal dimensions on this model. The results show that tortuosity and tortuosity fractal dimensions are conducive to improving the accuracy of the multi-peak pore structure model. The structure model, which can characterize the multi-scale and multi-peak distribution characteristics of shale pore diameter, provides a new concept for describing the pore structure of porous media.

Zircon U-Pb age of tuffaceous sandstone in the southern margin of Turpan-Hami Basin and its geological significance

The Dongdagou area of Yamansu in the southeastern margin of Turpan-Hami basin, which is located to the north of the Kangguertag collision zone, is one of the representative areas to discuss whether there is a Precambrian basement problem in the Junggar Turpan-Hami massif. As a consequence, zircon LA-ICP-MS U-Pb dating has been carried out for the shallow metamorphic tuffaceous fine sandstone in the Yamansu formation of the Lower Carboniferous in this area. The results show that the ages of 30 clastic zircons range from 365 ±3 Ma to 2451 ±39 Ma, with multi-peak distribution characteristics. The ages of clastic zircons are mainly concentrated in 365~496 Ma, the main peak is 365~436Ma, the secondary peak is 440~496 Ma, and the ages of 8 clastic zircons are between 765~2451 Ma. The study shows that the formation age of the sedimentary rock is not the early Carboniferous but the late Middle Devonian. Based on the isotopic dating data of the two-cloud quartz schist in the Xiaohuangshan area in the northeast of the study area, it is considered that the lower limit of the formation period of this set of strata is not earlier than the Devonian. Combined with the age data of ancient zircons in diabase and fused tuff in the study area, and the comprehensive analysis of regional sedimentary characteristics, it is concluded that there may be Precambrian crystalline basement in the sediment source area-Junggar-Turpan-Hami block.

Preparation of supramolecular viscoelastic polymers with shear, temperature, and salt resistance/sensitivity by amphiphilic functional monomer modification

To develop high-salinity, high-temperature reservoirs, a novel supramolecular viscoelastic polymer-based fracturing fluid modified with an amphiphilic functional monomer was developed. Investigation of the thickening ability, solubility, and rheology revealed that the as-developed gel system with a rigid hydrophobically associating space network structure and linear entanglement can improve the thickening ability, solubility, temperature adaptation range, and chemical environment resistance sensitivity of supramolecular polymers. The surface/interfacial tension test revealed that the modified polymers exhibit surface and interface activity. At an MHAP-15 concentration of 1500 mg/L, the surface tension was 39.29 Nm/m. At an MHAP-15 concentration of 800 mg/L, a minimum interfacial tension of 0.86 Nm/m was observed. The shear sensitivity test revealed that the copolymer fluid exhibits a high creep recovery performance and elastic response as well as a 100% viscosity recovery rate. In addition, the viscoelasticity and thixotropy of the copolymer solution were investigated. The results revealed that the higher the number of the oxyethylene groups in amphiphilic functional monomers, the higher the increase in the viscous modulus of the copolymer solution. In the modified polymer, the highest energy was required for the destruction of the MHAP-15 solution, reaching 66.5 Pa; this result confirmed the best synergistic effect of hydrophobic association and linear entanglement of the MHAP-15 solution molecules, as well as the best temperature and salt resistance. The viscosity of 0.6 wt% MHAP-15 was 120 mPa s after shearing for 50 min at 120 °C and at 170 s−1. At 160 °C and 100 s−1, the viscosity of the 0.8 wt% MHAP-15 polymer solution reached 153 mPa s after shearing for 50 min. At a NaCl concentration of 25 × 104 mg/L, the viscosities of the 0.6 wt% and 0.8 wt% MHAP-15 solutions were 203 and 245 mPa s, respectively, indicative of the stimulation response of salt thickening. At a CaCl2 concentration of 2 × 104 mg/L, the viscosity of 0.6 wt% MHAP-15 was 87 mPa s, and the viscosity retention rate was 47.9%. Finally, by X-ray diffraction, the particle size test in solution, and scanning electron microscopy, the higher the number of oxyethylene groups in the amphiphilic functional monomers, the higher the mixing entropy of copolymers, and the particle size in solution and multi-peak distribution were higher, as well as more clear linear entanglement between copolymers; all of these factors were conducive to the formation of large-scale supramolecular structures of super-bridged copolymers.

Numerical investigation of flow around two cylinders in tandem above a scoured bed

Flow mechanisms around two cylinders in tandem arrangement above a scoured bed have been investigated using the three-dimensional unsteady Navier–Stokes equations with the Spalart–Allmaras improved delayed detached-eddy simulation model. A turbulent inlet boundary layer generation method is adopted to obtain more realistic inlet boundary conditions. First, uniform flow over a single cylinder at Re = 3900 and flow over a single cylinder above scoured beds at Re = 6000 were simulated to validate the numerical model, boundary layer generation method, and mesh density effect. Second, two cylinders in the tandem arrangement above scoured beds with six different pitch ratios L/D are investigated numerically in terms of instantaneous vortex characteristics, the hydrodynamic force, and time-averaged flow fields. The simulation results in scoured beds are compared with simulations under the near flat wall and wall-free conditions. The major findings can be summarized as follows. (1) When L/D≤2.0, the wake of two tandem cylinders is dominated by the intermittent shedding, and the downstream sand dune in the scoured bed hinders the Kármán vortex formation at the rear of the downstream cylinder. Lift force fluctuations of the two cylinders have small amplitudes, and their spectra show a multi-peak distribution and no dominant peak frequency in the spectrum of the upstream cylinder. A squarish cavity-like recirculation zone is formed between two cylinders at L/D=2.0. (2) When L/D≥3.0, the periodic vortex shedding is evident in the wake of the upstream cylinder, and the small sand berm between two cylinders has an impact on the bottom shear layer of the upstream cylinder. The downstream cylinder is periodically impacted by the vortices shed from the upstream cylinder. Lift force spectra of the upstream and downstream cylinders have the same peak frequency. (3) Due to the influence of scoured bed and the inlet boundary layer, the time-averaged lift coefficient of the upstream cylinder remains negative when L/D≥1.5, and the critical spacing for drag inversion is relatively smaller compared with under wall-free conditions. The negative pressure coefficient values of the upstream cylinder are smaller than the values in near flat wall and wall-free conditions.

Pair-Copula-based trivariate joint probability model of wind speed, wind direction and angle of attack

The temporal and spatial distribution of wind fields in the deep-cut gorge bridge site is complex, and the impact of different incoming flows on the structure is also essentially different. Therefore, it is essential to comprehensively consider the correlation between wind direction, wind speed, and angle of attack. The joint probability models between average wind parameters are first established using the Pair-Copula decomposition based on the field-measured data. Then, the concept of the probability-segmentation-based first order inverse reliability method (PSB-IFORM) is proposed for calculating the environmental surface of the multi-peak joint distribution model. The results show that the mixed von Mises distribution is ideal to fit the wind direction with multi-peak characteristics. The trivariate joint probability model constructed in this paper ultimately represents the correlation of average wind parameters, and the most unfavorable combination of design wind parameters can be found on the environmental surface. Furthermore, the proposed PSB-IFORM can effectively avoid the defects of the inverse first-order reliability method (IFORM) and the conservative highest probability contour (HDC) method in solving the multi-peak joint probability distribution model. This study is of particular interest to researchers and engineers engaged in wind resistance of mountain structures.

A microenvironment prediction model for Chinese solar greenhouses based on the bond graph approach.

To improve the prediction accuracy of temperature and humidity in typical Chinese solar greenhouses, this paper proposed a new longwave/shortwave radiation modeling method using bond graph. This model takes into account sun position, useful incoming solar radiation model, sky longwave radiation model, inside longwave, and shortwave radiation model. The approach solves the problems caused by underestimating the effects of longwave radiation on night temperature and relative humidity. The study found that after a period of t = 7.5 h, with the increase of sun altitude angle, the internal temperature was significantly affected by the temperature rise of outside environment on sunny day. The sun altitude angle gradually falls over a period of t = 12.5 h (beginning at 12.30 p.m.). The decline in night temperature steadily slowed after a period of t = 20.5 h. On the other hand, the temperature variation has a multi-peak distribution and the warming rate of the CSG slows down on cloudy days. Furthermore, a good agreement between the experimental and simulation data were obtained, with a maximum temperature deviation of 2°C and maximum humidity deviation of 5%. The developed model is a universal and valuable approach that can be used for greenhouse climate simulation. Furthermore, it can be used as a support system during decision-making processes to help manage Chinese solar greenhouses more efficiently, which provides several control perspectives on the low-energy greenhouse in the future. This work has also provided several control perspectives on the low energy greenhouse in the future.