Uniform Design Method Research Articles

Study on Preparation and Characterization of Graphene Based on Ball Milling Method

Taking advantage of the state-of-the-art graphene preparation technologies in China and abroad, this work studied the preparation processes of graphene for road applications based on the preliminary high-speed vibration ball milling method. This work combined numerical modeling and microscopic experiments. The preparation parameters were optimized through a multifactor and multilevel test scheme. The materials, influencing factors, and parameters in the preparation process were systematically studied. A graphene preparation method was proposed that considered vibration frequency, static filling rate, material-to-ball volume ratio, and the void percentages of media. Flake graphite, aluminum powder, and 304 stainless-steel grit were used as the preparation materials. The preparation parameters and process model were established based on the uniform design method. The preparation parameters were proposed, calculated, and optimized. Microscopic analysis showed that the proposed preparation method can improve the quality of graphene. This study provides a new source of raw materials for the application of graphene in road engineering.

Proportion optimization of grouting materials for roadways with soft surrounding mass

ABSTRACT Severe deformation and failure frequently occur in roadways with soft or weak surrounding rock and have greatly influenced safe and efficient mining of coal in many coal mines. Using portland cement, emery and fly ash as main raw materials, through laboratory tests, effect of water/binder ratio, cement/sand ratio, water/sodium silicate ratio, water-reducing agent, fly ash/cement ratio, and various performance indexes of grout of fluidity, viscosity, setting time, bleeding rate, compressive strength, concretion rate, and various performance indexes were systematically analyzed. An optimized mixture ratio of the main raw materials added in the grouting material proportion was determined through uniform design method, an optimal mixture ratio was determined by regression analysis. The results show that: 1) The flow performance is significantly affected by change of sodium silicate and water reducer, the compressive strength of grouting material increases significantly with increase in emery content, and decreases significantly with increase in water reducer. 2) An optimized mixture ratio among water-cement ratio, cement-sand ratio, water/sodium silicate ratio, water-reducing agent, fly ash/cement ratio in the grouting material is 0.75, 1.2, 0.08, 0.03, and 0.18, respectively. Field test demonstrated that the material has better performance in reinforcing weak and broken rock mass.

An Investigation of the Laser Welding Process for Dual-Phase Steel via Regression Analysis

In this work, a systematic investigation was undertaken to explore the effects of welding process parameters on the mechanical performances of the welding joints in the laser welding process for DP600. Welding experiments were arranged by a uniform experimental design method with four control factors (laser power, welding speed, focal point position, and side-blowing shield gas flow). The tensile strength of the welding joints was used to quantify the welding quality. A mathematical model based on stepwise regression analysis was employed to correlate the welding process parameters and the tensile strength. The effects of the welding process parameters on the welding quality were discussed. The genetic algorithm was then employed to select the optimum welding parameters. The verification test results proved that the method proposed in this paper could effectively evaluate and optimize the welding quality within the range of process parameters, which could enhance the welding performance in the laser welding process as feasibly and effectively as possible.

Discovery and proteomics analysis of effective compounds in Valeriana jatamansi jones for the treatment of anxiety

Ethnopharmacological relevanceZhizhu Xiang (ZZX for short) is the root and rhizome of Valeriana jatamansi Jones, which is a Traditional Chinese Medicine (TCM) used to treat various mood disorders for more than 2000 years, especially anxiety. However, there have been few investigations to clarify the compounds in ZZX for the treatment of anxiety. Aim of the studyOur previous study has identified five anti-anxiety components, including hesperidin, isochlorogenic acid A, isochlorogenic acid B and isochlorogenic acid C and chlorogenic acid, from extract of ZZX. In order to find the optimal combination and the underlying mechanism of these five components in the treatment of anxiety disorder, researches were designed based on uniform design method and proteomic technology. Materials and methodsThe samples with different proportion and content of the five active components were arranged by uniform design method. Then a mathematical model was formulated using partial least square method and stepwise regression analysis. Moreover, the empty bottle stress-induced anxiety rat model was established, and the anti-anxiety effect was recorded by the unconditioned reflex elevated maze test and the open field test. In addition, the isobaric tags for relative and absolute quantitation (iTRAQ) technique, along with the multidimensional liquid chromatography and high-resolution mass spectrometry were applied in proteomic study. At last, the result of proteomic analysis was further confirmed by Western blot. ResultsThe optimal combination of the components from the extract of ZZX was 1.153 mg/kg hesperidin, 2.197 mg/kg Isochlorogenic acid A, 0.699 mg/kg Isochlorogenic acid B and 1.249 mg/kg Chlorogenic acid. Total 6818 proteins were identified using proteomic analysis and 80 differentially expressed proteins were used for further bioinformatic analysis. These proteins were involved in the neuroactive ligand-receptor interaction, protein digestion and absorption, cholesterol metabolism, Chagas disease, and AGE/RAGE signaling pathway. ConclusionsThe composition and proportion of anti-anxiety components in extract of ZZX was disclosed, and there was an anti-anxiety effect for the combined components of flavonoids and phenolic acids. Through proteomic analysis and Western blot, it was found that the effective components of extract of ZZX can exert synergistic anti-anxiety effects via the regulation of multi-signaling pathways. These findings could provide a preliminary research basis for the development of new low-toxic, efficient, stable and controllable anti-anxiety drugs.

Formulation of a new warm-mix recycling agent and its rejuvenating effect on aged asphalt

Warm-mix recycling asphalt mixture has remarkable environmental and economic benefits. In this study, a new warm-mix recycling agent (WR) was developed by using base oil (80%), surfactant (9.5%), plasticizer (8.0%) and antiaging agent (2.5%) based on uniform design method. Experimental tests including penetration, softening point, ductility, elastic recovery, dynamic shear rheometer (DSR), multiple stress creep recovery (MSCR), bending beam rheometer (BBR), linear amplitude sweep (LAS), rotational viscosity as well as Fourier transform infrared spectroscopy (FTIR) test were conducted to evaluate the properties of aged binders incorporating the WR and other two commercial rejuvenators, i.e. an emulsified rejuvenator (ER) and a resinous rejuvenator (RR). Additionally, the workability and cost of reclaimed asphalt binders were analyzed. Results indicate that the WR is able to rejuvenate conventional physical properties of aged asphalt. Reclaimed asphalt containing WR shows the best low-temperature performance and longest fatigue life than that containing other two commercial rejuvenators. With regard to high-temperature performance, reclaimed asphalt incorporating WR compares favorably with that incorporating ER. The results from FTIR test demonstrated that physical interaction dominated the rejuvenation of aged asphalt after adding the WR. WR can significantly replenish the volatiles in aged asphalt, and restore its components’ proportion that resembles the virgin asphalt. In comparison with ER and RR, WR exhibits a lower increased cost and the excellent capability of reducing mixing and compaction temperature.

Effect of Mixed Commercial Cold Flow Improvers on Flow Properties of Biodiesel from Waste Cooking Oil

The uniform design method was used to screen the solidifying point depressing effects of 18 traditional diesel cold flow improvers on biodiesel derived from waste cooking oil. The cold flow improvers with good effects were selected for orthogonal optimization. Finally, the mixed cold flow improver (CFI) with the best depressing effect was selected to explore its depressing mechanism for biodiesel. The results show that the typical CFIs such as A132, A146, 10-320, 10-330, A-4, CS-1, AH-BSFH, Haote, T1804D, and HL21 all have a certain solidifying point depressing effect on biodiesel, while other cold flow improvers had no obvious effect. Amongst them, 10-330 (PMA polymer) and AH-BSFH (EVA polymer) had better solidifying point depressing effects over others, both of which reduced the solidifying point (SP) of biodiesel by 4 °C and the cold filter plugging point (CFPP) by 2 °C and 3 °C, respectively. From the orthogonal mixing experiment, it can be seen that the combination of 10-330 and AH-BSFH at a mass ratio of 1:8 had the best depressing effect, reducing the solidifying point and cold filter plugging point of biodiesel by 5 °C and 3 °C, respectively. Orthogonal analysis showed that when used in combination, AH-BSFH had a greater impact on the solidifying point, while the ratio of the combination had a greater impact on the cold filter plugging point.

Oxidative stress, growth inhibition, and DNA damage in earthworms induced by the combined pollution of typical neonicotinoid insecticides and heavy metals

Heavy metals pollution of soil and widespread application of neonicotinoid insecticides have caused environmental problems worldwide. To evaluate ecological toxicity resulting from the combined pollution of neonicotinoids and heavy metals, typical representatives of neonicotinoid insecticides (imidacloprid, thiamethoxam, dinotefuran) and heavy metals (cadmium, copper, zinc) were selected as soil pollutants; earthworms were used as test organisms. Analysis of the main and interaction effects of a combined pollution process were performed using a uniform design method. Results showed that the reactive oxygen species (ROS) content of earthworms in most treatment groups was higher during exposure than that of the control group. The malondialdehyde (MDA) and ROS content of earthworms demonstrated relatively low values on the 21st day and increased by the 28th day. The interaction between dinotefuran and Cd had significant antagonistic effects on ROS and MDA. The combined pollution adversely affected both the growth and genes of earthworms and also caused damage to the epidermis, midgut, and DNA. The interaction between imidacloprid and Cd was synergistic to ROS, weight inhibition rate, and Olive tail moment (OTM), but was antagonistic to MDA. Of all the single and combined exposures, Zn as a single chemical affected ROS and DNA damage the most, and MDA was significantly enhanced by imidacloprid. Composite pollutants may create different primary effects and interactions causing potential harm to soil organisms.

Error prediction and structure determination for CMAC neural network based on the uniform design method

AbstractInsufficient study on error bound of cerebellar model articulation controller (CMAC) severely limits its application. To investigate the error prediction and structure determination of CMAC for multi‐dimensional and data‐generation objects, this paper builds a 10‐input 2‐output model for a desulfurization system to test 44,640 sets of operation data. Four test groups and one prediction group are designed and performed based on uniform design method. Regression analysis and curve fitting methods are applied for error analyses. The focus of regression analysis method is the influence of uniform table's level on its prediction formulas' accuracies, whereas curve fitting's is the impact of theoretical memory space (location number) and actual storage space (address number) of CMAC on output error. Based on the results, the following conclusions are obtained. (a) The prediction accuracy of the linear regression equation is not monotonous with the level of the uniform design table, but there is a distinct region with local high precision. (b) Compared with regression analysis and address number fitting methods, location number analysis method has distinct advantages of prediction range, accuracy and flexibility. (c) In terms of location number analysis, different intervals may correspond to different optimal fitting functions, but only power function maintains high prediction accuracy in the whole range where the method works. Besides, the scope of location number analysis is also studied, of which the lower borders are 109 and 1010 approximately for model's two outputs, respectively.

An Online AM Quality Estimation Architecture From Pool to Layer

Quality control is the key for the widespread adoption of metal additive manufacturing (AM). However, online quality estimation is challenging because high-frequency stream data derived from in situ metrology have to be processed in a timely manner to figure out the complicated interactions among material, machine, and part. To tackle such issue, this article proposes an intelligent AM metrology (IAMM) architecture to decouple and evaluate quality variations caused by material properties, machine issues, and process parameters when building an AM part. The IAMM architecture can also estimate the online layer-to-layer quality (e.g., roughness and density of an AM part) by applying the robust parameters derived from the uniform design (UD) method via the enhanced automatic virtual metrology technology in a parallel computing environment, as soon as the microfeatures of melt-pools and the macrofeatures of each layer are extracted. In addition, the associated indices and features in the IAMM architecture can also be used to evaluate the defects caused by machine issues in the given process parameters. The results of case studies validate the applicability of the IAMM architecture and show that the proposed estimation models are prospective for future closed-loop control in an AM process. Note to Practitioners —The proposed intelligent AM metrology (IAMM) architecture can be implemented modularly in a metal additive manufacturing (AM) machine that possesses the capability of estimating the coating and printing qualities of the AM process by extracting features from the optical data of the melt pools and chamber layer by layer. The estimated indices and qualities can be derived online using parallel computation to timely diagnose the machine issues and control the process of the next layer. Hence, when an AM machine is equipped with the IAMM architecture, it can efficiently manufacture a 3-D part with reduced defects in real time.

Composition Optimization and Field Application of Colored Emulsified Asphalt Seal Mixture

A uniform test design method was used to investigate the storage stability, wear resistance performance, anti-slide performance, and color durability of a colored emulsified asphalt seal mixture (CEASM). The optimal mix proportions of the seal mixture were determined, and the engineering test application and effect evaluation analysis were performed. The results show that the clay, silica fume, pigment, mineral aggregate, and emulsified asphalt contents in the prepared mixture ranged from 15–17%, 12–16%, 10–14%, 28–32%, and 25–32%, respectively. In practical engineering applications, CEASM with a molding thickness of 2–3 mm stored in liquid form has a good storage stability and wear resistance, which is suitable for manual scraping pavement or mechanical spraying construction. In addition, it has been shown that colored pavement has the advantages of low cost, safety, environmental protection, convenient construction, good durability, and rapid molding. The CEASM also has great application prospects in color repaving for non-color roads, the early maintenance of colored pavement, and road disease maintenance. The results guide colored pavement designs to improve the storage stability of CEASM and enhance the color durability and crack resistance of colored pavements.

Prediction method of bridge static deformation based on dynamic test

AbstractTo solve the high cost of bridge load tests, considerable influence on traffic, and damage to bridge structure in the process of problem detection and maintenance of existing bridges, we use the method of improved Gaussian process response surface to explore the prediction of the rigidity and unit weight of existing bridges to produce high‐precision predictions of the existing bridge static test. The Gaussian process response surface method in Bayesian principle is adopted to optimize and correct the model. Because Gaussian process is a non‐parameter model with high sensitivity, reliable accuracy, and small calculation, it avoids repeatedly using finite element model. This makes the efficiency of finite element correction improve significantly. A continuous beam bridge is adopted as a study case. In sample selection, an improved uniform design method based on weighting is designed to improve the learning efficiency and prediction accuracy of the model while using ANSYS to analyze and predict the typical bridge. The analysis of the date of the bridge dynamic test is used to correct the finite element model, obtain the actual parameters of the bridge structure, and predict the measured data of the bridge static load test based on the modified finite element model.

Preparation of high friction brake shoe material and its tribological behaviors during emergency braking in ultra-deep coal mine hoist

The ultra-deep coal mine exhibits the larger speed (>18 m/s) and terminal load (≥240 t/cycle) during hoisting as compared to the ordinary deep coal mine. The larger coefficient of friction and brake specific pressure between brake shoe and brake disc are required to provide the larger friction force and brake torque in order to realize the safe and reliable braking. Therefore, the preparation of high friction brake shoe material and its tribological behaviors during emergency braking in ultra-deep coal mine hoist were investigated in this study. The tribo-brake test rig of brake shoe material with the maximum speed 20 m/s and maximum specific pressure of 2.0 MPa was developed based on the similarity principle. Mechanical properties and conventional tribological behaviors (coefficient of friction, wear rate, temperature rise rate, surface morphology and composition) of resin based brake shoe materials of different formulas were investigated to obtain the optimal formula of high friction brake shoe material employing the uniform experimental design method. Conventional tribological properties of self-made and commonly used WSM-3 brake shoe materials were compared. Effects of initial braking speed and brake specific pressure on tribological behaviors of high friction brake shoe material during emergency braking with the large speed and brake specific pressure were explored. The results show that the optimal formula of brake shoe material consists of the optimal basic formula (phenolic resin 9.8%, NBR 3.8%, vermiculite powder 4.9%, conductive carbon black 2.6%, ceramic fiber 10.6%, graphite 3.8%, sepiolite 8.7%, wollastonite 19.2%, barium sulfate 10.6%, diatomite 7.9%, stearic acid 1.5%, zircon 4.5%, mica 3.8%, kaolin 3%, antimony trioxide 3%, and lead oxide 2.3%), graphene 4%, carbon fiber 2% and glass fiber 4%. As compared to WSM-3 brake shoe materials, the high friction brake shoe material presents the higher coefficient of friction and the medium volume wear rate. During emergency braking, the average coefficient of friction at the stabilized stage shows an increase at first and then a decrease with increasing initial braking speed, and a decrease with increasing brake specific pressure. Increases of initial braking speed and brake specific pressure cause increases in the temperature and temperature rise amplitude of friction disc surface.

Optimized Portable Unilateral Magnetic Resonance Sensor for Assessing the Aging Status of Silicon Rubber Insulators

Silicone rubber insulators (SRIs) play an important role in high-voltage power transmission lines. Given that SRIs critically threaten the safe operation of the power grid, quantitatively assessing the aging status of SRIs in situ is crucial. In this article, a portable unilateral magnetic resonance (UMR) sensor with a U-shaped magnet structure and its measuring circuit were designed for the nondestructive detection of the aging status of SRIs in situ. First, the optimization efficiency of the magnet structure was improved through a uniform design method. Then, the planar radio frequency (RF) coil was designed by the finite-element method. Furthermore, the demagnetization effect of eddy currents induced in metal materials on the RF magnetic field was analyzed. We measured the SRI sheds at different service times and obtained the corresponding 1H transverse relaxation decay curves by importing the Carr- Purcell-Meiboom-Gill (CPMG) sequence. Finally, the transverse relaxation decay curves were postprocessed using inverse Laplace transformation, and the 1-D spectrum distributions of transverse relaxation time (T2) were obtained. The results reveal that T2 of the surface of the SRI shed decreases as the service time of the SRI increases. In addition, the difference in T2 between the surface and interior of the SRI shed increases. The comparison experiments demonstrate that the U-shaped sensor designed in this article is superior to the curved sensor previously designed by our team. The effect of temperature variation on SRIs aging assessment was considered at last.

Study on the wind-induced fatigue of heliostat based on the joint distribution of wind speed and direction

Heliostats are a kind of reflection devices in solar power tower plants, and are generally arranged in flat and open areas, with independent column structure. Because the angle needs to be adjusted continuously during the use, heliostats are subject to large wind load and their support structure is prone to wind-induced fatigue. In this work, a joint distribution model was established according to the law of heliostat tracking the sun and combining with the data on wind direction and wind speed at the local meteorological station. The mixed uniform design method was used to design the research conditions, and Ansys Workbench and nCode Design Life software were coupled to combine the finite element analysis with the wind tunnel test of the heliostat structure, so as to analyze the wind-induced fatigue of the heliostat support structure. The GBDT algorithm was adopted to fit the fatigue life in typical working condition, estimate its fatigue life and analyze the law. In this work, the fatigue analysis of the heliostat support structure was conducted through a combination of mixed uniform design and finite element analysis, so as to reduce the test conditions, improve the test efficiency and estimate the fatigue life, and provide a basis for engineering design.

Response surface method based on uniform design and weighted least squares for non‐probabilistic reliability analysis

AbstractThe non‐probabilistic reliability theory is a promising methodology for implementing structural reliability analysis in case of scarce statistical data. One of the main obstacles to implement non‐probabilistic reliability analysis is the implication of the limit state function (LSF) for complex structures. This paper aims to establish a surrogate model of the LSF with higher simulation precision, and whereby proposes a response surface method based on the combination of uniform design (UD) and weighted least squares (WLS). At first, the UD method is selected as the sampling method of interval variables to realize the uniform space‐filling of the initial samples, and the sample set is updated by gradually adding the approximate optimal points to increase the sampling density of critical domain. Then, the WLS method is applied to improve the precision of the response surface by adjusting the importance of samples to the function fitting. Finally, a method of constructing sample weights is developed. Two examples are applied to validate the feasibility and efficiency of the proposed method. Results show that the proposed method is effective for non‐probabilistic reliability analysis of complex structures owning to high computational precision and low computational cost in both numerical and case study.

Optimization Scheme of Hydraulic Fracturing Simulation Experiments using Mixed-level Uniform Design Method Based on the PKN model

This paper aims at revealing the hydraulic fracturing effect of hydrodynamic influencing factors of fracturing fluid by laboratory experiments. The experimental design for huge number of hydrodynamic influencing factors with many levels, is oftentimes incorporated with the conventional methods, i.e. Based on the PKN model, injection rate, viscosity, and density (of the fracturing fluid) and their parameter values (levels) were considered for the construction of an optimal mixed-level design table U* 12(43×6), which constructed the optimization scheme. The experiments results were subjected to multiple regression analysis to establish optimal fitting formulas for the relationship of single factor or multi-factor with rock fracturing value. Compared with other experimental designs, experimental number of U* 12(43×6) yielded only half the number of experiments in the orthogonal design L24(43×6) and presented better distribution uniformity of experimental points than Ui2(43×6). This paper provides a fast and effective experimental scheme for the effect analysis, as well as a substantially accurate method for in-situ stress measurement.

A Novel Recyclable Alkaline Biphasic 2-Phenoxyethanol/Water System for Rice Straw Biorefinery under Mild Conditions

A novel recyclable alkali-assisted biphasic pretreatment process under mild conditions with low water consumption is first developed. After conditions were optimized with the uniform design method,...

PREDICTION AND OPTIMIZATION OF A DESULPHURIZATION SYSTEM USING CMAC NEURAL NETWORK AND GENETIC ALGORITHM

In this paper, taking desulphurizing ratio and economic cost as two objectives, a ten-input two-output prediction model was structured and validated for desulphurization system. Cerebellar model articulation controller (CMAC) neural network and genetic algorithm (GA) were used for model building and optimization of cost respectively. In the model building process, the grey relation entropy analysis and uniform design method were used to screen the input variables and study the model parameters separately. Traditional regression analysis and proposed location number analysis method were adopted to analyze output errors of experiment group and predict the results of test group. Results show that regression analyses keep high fit degree with experiment group results while the fitting accuracies for test group are quite different. As for location number analysis, a power function between output errors and location numbers was fitted well with the data of experiment group and test group for SO2. Prediction model was initialized by location number analysis method. Model was validated and cost optimization case was performed with GA subsequently. The result shows that the optimal cost obtained from GA could be reduced by more than 30% compared with original optimal operating parameters under same constraints.

Multidisciplinary integrated design of long-range ballistic missile using PSO algorithm

In the case of the given design variables and constraint functions, this paper is concerned with the rapid overall parameters design of trajectory, propulsion and aerodynamics for long-range ballistic missiles based on the index of the minimum take-off mass. In contrast to the traditional subsystem independent design, this paper adopts the research idea of the combination of the subsystem independent design and the multisystem integration design. Firstly, the trajectory, propulsion and aerodynamics of the subsystem are separately designed by the engineering design, including the design of the minimum energy trajectory, the computation of propulsion system parameters, and the calculation of aerodynamic coefficient and dynamic derivative of the missile by employing the software of missile DATCOM. Then, the uniform design method is used to simplify the constraint conditions and the design variables through the integration design, and the accurate design of the optimized variables would be accomplished by adopting the uniform particle swarm optimization (PSO) algorithm. Finally, the automation design software is written for the three-stage solid ballistic missile. The take-off mass of 29 850 kg is derived by the subsystem independent design, and 20 constraints are reduced by employing the uniform design on the basis of 29 design variables and 32 constraints, and the take-off mass is dropped by 1 850 kg by applying the combination of the uniform design and PSO. The simulation results demonstrate the effectiveness and feasibility of the proposed hybrid optimization technique.

Optimization of Preparation Method of Molecularly Imprinted Microspheres by Uniform Design

This work presented a simple and effective method for the preparation of molecularly imprinted microspheres (MIMPs) through multi-step swelling polymerization. To prepare carbofuran MIMP with a uniform size, the experiment of optimizing the dosage of reagents which used during synthesis based on uniform design (UD) method was performed. Six kinds of factors, namely methacrylic acid (MAA, functional monomer), ethylene glycol dimethacrylate (EGDMA, cross linker), polyvinyl alcohol (PVA, dispersant), dibutyl phthalate (DBP, sweller), polymerization temperature and polymerization speed were taken into account based on UD to perform the optimization experiment. The micromorphology of MIMP was characterized by scanning electron microscopy (SEM) and it showed that the particle sizes were between 6-8 μm. The results indicated that MIMP possessed good selectivity and specificity for carbofuran, which was an excellent material for adsorption and testing of carbofuran residues in food and environment.