Blending Machine Research Articles

Exploration of a new AlCoCrNiNb high-entropy alloy: in situ alloying of a CoCrMo, M247, and Nb powder mixture via laser powder bed fusion

AbstractHigh-entropy alloys (HEAs) have compelling advantages, such as high strength and corrosion resistance, but they remain underexplored owing to the limited availability of certain prealloyed and elemental powders. In this study, an AlCoCrNiNb HEA was fabricated in situ via laser powder bed fusion (LPBF) using a powder mixture of commercial CoCrMo, Mar M247, and Nb elemental powders. The powder mixture was blended for 24 h using a horizontal blending machine, to obtain similar chemical compositions in the middle and top layers of the blended powder. However, local Nb aggregation was observed in the bottom layer owing to the particle-size effect. X-ray diffraction and chemical composition analyses revealed that the in situ alloyed AlCoCrNiNb HEA specimen obtained via LPBF was a homogeneous solid solution with a face-centered cubic structure. HEA exhibits a fine-grained morphology, and its maximum microhardness is approximately 970 HV. These characteristics are typical of rapid solidification and sluggish diffusion. These results underscore the effectiveness of using commercial prealloyed and elemental powders for fabricating AlCoCrNiNb HEAs through LPBF-based in situ alloying, thus advancing the development of HEAs. Thermodynamic calculations were performed to support these outcomes.

Flash flood susceptibility mapping based on catchments using an improved Blending machine learning approach

Abstract Flash floods are a frequent and highly destructive natural hazard in China. In order to prevent and manage these disasters, it is crucial for decision-makers to create GIS-based flash flood susceptibility maps. In this study, we present an improved Blending approach, RF-Blending (Reserve Feature Blending), which differs from the Blending approach in that it preserves the original feature dataset during meta-learner training. Our objectives were to demonstrate the performance improvement of the RF-Blending approach and to produce flash flood susceptibility maps for all catchments in Jiangxi Province using the RF-Blending approach. The Blending approach employs a double-layer structure consisting of support vector machine (SVM), K-nearest neighbor (KNN), and random forest (RF) as base learners for level-0, and the output of level-0 is utilized as the meta-feature dataset for the meta-learner in level-1, which is logistic regression (LR). RF-Blending employs the output of level-0 along with the original feature dataset for meta-learner training. To develop flood susceptibility maps, we utilized these approaches in conjunction with historical flash flood points and catchment-based factors. Our results indicate that the RF-Blending approach outperformed the other approaches. These can significantly aid catchment-based flash flood susceptibility mapping and assist managers in controlling and remediating induced damages.

Tooth surface Hobbing analysis for unconventional gears with ultrasonic-assisted motion

As an atypical conventional gear pair, non-circular gear has a variable transmission ratio, which can be used to improve the structure and transmission characteristics in some applications, such as variable speed grinding mechanism, wool blending machine guide mechanism, continuously variable transmission structure and so on. According to the friction theory of conjugate surfaces, the transmission characteristics will be affected by the micro topography of tooth surface, but the shaped tooth surface of non-circular gear with normal hobbing method is not uniform, because of its variable radius and flank orientations of tooth surface. The research on the relationship between micro topography and parameters of non-circular gear is necessary, thus an improved manufacturing method with ultrasonic-assisted motion was presented in this paper, the mathematical equations for the theoretical tooth surface of non-circular gear with and without ultrasonic-assisted motion have been derived in this paper, also the equations for cutting parameters (step displacement, step rotating angle) have been proposed, shown that all the parameters (initial parameters of gear and gear hob, cutting parameters in manufacturing process) will affect the formed micro surfaces. In detail, the height Hm and width Sm of micro undulating tooth surface periodically increase and decrease, getting the maximum value at θn=π, where is the maximum radius. The height Hm and width Sm of micro tooth surface will increase with any control parameter increase, the height Hm of most micro peaks is near 6.5um in normal hobbing process. While, the tooth surface with ultrasonic-assisted motion is more regular and clearer with the maximum height Hm decrease from 6.5 um to 2.7 um, getting more compact cutting tracks and lower surface roughness. The experimental results shows that ultrasonic-assisted hobbing has obviously positive influence for micro tooth surface, provides the theoretical support for a further analysis and better application of unconventional gear pair.

Combinatorial Benders decomposition for melted material blending systems considering transportation and scheduling

We study an integrated optimisation problem with blending, scheduling, and routing components for a melted material blending production system. The problem is formulated as a mixed-integer linear programming model that considers the blending machine environment, due dates, target amounts, required chemical compositions of the products, and ready times of the materials in containers. This model aimed to determine the container pairings, blending plants for container pairs, and schedules for blending operations while minimising the total end time of material usage, total penalty for violating component specifications, and employee workload. Further, we propose a three-stage approach that involves solving a relaxed problem and then resolving the problem with fixed variables. We developed a combinatorial Benders decomposition algorithm with a minimal infeasible subsystem identification algorithm for the blending scheduling problem. The experimental results indicate that the proposed method can find high-quality solutions within a reasonable amount of time.

Biochemical changes associated with the administration of aqueous pulp extract of Irvingia gabonensis fruit on adult male Wistar rats

Biochemical changes associated with the administration of aqueous pulp extract of Irvingia gabonensis fruit on adult male Wistar rats

Development and validation of a novel blending machine learning model for hospital mortality prediction in ICU patients with Sepsis

BackgroundEarly prediction of hospital mortality is crucial for ICU patients with sepsis. This study aimed to develop a novel blending machine learning (ML) model for hospital mortality prediction in ICU patients with sepsis.MethodsTwo ICU databases were employed: eICU Collaborative Research Database (eICU-CRD) and Medical Information Mart for Intensive Care III (MIMIC-III). All adult patients who fulfilled Sepsis-3 criteria were identified. Samples from eICU-CRD constituted training set and samples from MIMIC-III constituted test set. Stepwise logistic regression model was used for predictor selection. Blending ML model which integrated nine sorts of basic ML models was developed for hospital mortality prediction in ICU patients with sepsis. Model performance was evaluated by various measures related to discrimination or calibration.ResultsTwelve thousand five hundred fifty-eight patients from eICU-CRD were included as the training set, and 12,095 patients from MIMIC-III were included as the test set. Both the training set and the test set showed a hospital mortality of 17.9%. Maximum and minimum lactate, maximum and minimum albumin, minimum PaO2/FiO2 and age were important predictors identified by both random forest and extreme gradient boosting algorithm. Blending ML models based on corresponding set of predictors presented better discrimination than SAPS II (AUROC, 0.806 vs. 0.771; AUPRC 0.515 vs. 0.429) and SOFA (AUROC, 0.742 vs. 0.706; AUPRC 0.428 vs. 0.381) on the test set. In addition, calibration curves showed that blending ML models had better calibration than SAPS II.ConclusionsThe blending ML model is capable of integrating different sorts of basic ML models efficiently, and outperforms conventional severity scores in predicting hospital mortality among septic patients in ICU.

Effects of Active Food Media on Properties of Materials Usedin Local Food Processing Machine

Food contains edible biochemical compounds, which serves as sources of nutrients to human being. However, their contamination through processing can bring about adverse effects on humans when consumed. Food blending is one of the major processing done in preparing edible meals. The effect of active food media on the material used in fabricating the grinding shaft of the blending machine cannot be ignored taking into consideration the resultant subsequent effects on blended food. Some of the effects of active food media on metallic parts of food blending machines are protein adhesion, abrasive effect, reduction in mechanical properties and conditions favouring corrosion. Three types of food materials, onion, pepper, and tomato, were chosen to be the focus of this study owing to the prevalence index of their processing amongst the local communities. They were processed using a selected blending machine while the ultimate analyses and determination of elemental compositions were carried out on the processed samples. The mean values of ascorbic acid from four runs of onion, pepper, and tomato samples through a blending machine were found to be 5.94 mg/100ml, 13.13 mg/100ml, and 16.99 mg/100ml, respectively. Some other mineral elements, such as iron, calcium, sodium, potassium and magnesium, were found in varied compositions as the number of blending runs increased. The results obtained showed that these food items contain active ingredients and complex compounds which have gross effect on the mild steel used in fabricating the grinding shaft of the blending machine.

Multi-Agent Systems for Search and Rescue Applications

The goal of this review is to evaluate the current status of multi-robot systems in the context of search and rescue. This includes an investigation of their current use in the field, what major technical challenge areas currently preclude more widespread use, and which key topics will drive future development and adoption. Work blending machine learning with classical control techniques is driving progress in perception-driven autonomy, decentralized multi-robot coordination, and human–robot interaction, among others. Ad hoc mesh networking has achieved reliability suitable for safety-critical applications and may be a partial solution for communication. New modular and multimodal platforms may overcome mobility limitations without significantly increasing cost. Multi-agent systems are not currently ready for deployment in search and rescue applications; however, progress is being made in a number of critical domains. As the field matures, research should focus on realistic evaluations of constituent technologies, and on confronting the challenges of simulation-to-reality transfer, algorithmic bias in autonomous agents that rely on machine learning, and novelty-versus-reliability incentive mismatch

Computational and Experimental Approaches for Determining Scattering Parameters of OPEFB/PLA Composites to Calculate the Absorption and Attenuation Values at Microwave Frequencies.

This article describes attenuation and absorption measurements using the microstrip transmission line technique connected with a microwave vector network analyzer (Agilent 8750B). The magnitudes of the reflection (S11) and transmission (S21) coefficients obtained from the microstrip transmission line were used to determine the attenuation and absorption of oil palm empty fruit bunch/polylactic acid (OPEFB/PLA) composites in a frequency range between 0.20 GHz and 12 GHz at room temperature. The main structure of semi-flexible substrates (OPEFF/PLA) was fabricated using different fiber loading content extracted from oil palm empty fruit bunch (OPEFB) trees hosted in polylactic acid (PLA) using the Brabender blending machine, which ensured mixture homogeneity. The commercial software package, Computer Simulation Technology Microwave Studio (CSTMWS), was used to investigate the microstrip line technique performance by simulating and determine the S11 and S21 for microwave substrate materials. Results showed that the materials’ transmission, reflection, attenuation, and absorption properties could be controlled by changing the percentage of OPEFB filler in the composites. The highest absorption loss was calculated for the highest percentage of filler (70%) OPEFB at 12 GHz to be 0.763 dB, while the lowest absorption loss was calculated for the lowest percentage of filler 30% OPEFB at 12 GHz to be 0.407 dB. Finally, the simulated and measured results were in excellent agreement, but the environmental conditions slightly altered the results. From the results it is observed that the value of the dielectric constant ( and loss factor ( is higher for the OPEFB/PLA composites with a higher content of OPEFB filler. The dielectric constant increased from 2.746 dB to 3.486 dB, while the loss factor increased from 0.090 dB to 0.5941 dB at the highest percentage of 70% OPEFB filler. The dielectric properties obtained from the open-ended coaxial probe were required as input to FEM to calculate the S11 and S21 of the samples.

Effect of Several Exterior Adhesive Types on Dimensional Stability of Bamboo Oriented Particleboard

The objective of this research is to evaluate the effect of adhesive types on dimensional stability of bamboo-oriented particleboard. The materials used in this research are bamboo tali(Gigantochloa apus J.A & J.H. Schult. Kurz), UF/MDI(8, 10, 12 % level), and MF, MDI, and PF at 7 % level. Particle and adhesive are mixed using a blending machine; then, mat forming and hot pressing processes are performed using adhesive-suitable temperature and time references. MDI resin is set at 160 °C temperature for 5 minutes. PF resin and MF resin are pressed at 170 °C for 10 minutes, and 140 °C for 10 minutes, respectively, while UF/MDI sets at temperature of 140 °C for 10 minutes. The results show that particleboard using PF resin produces the lowest thickness swelling value. The particleboard using UF/MDI resin also produces good response for thickness swelling value. Interesting things happen in that UF/MDI adhesive produces a thickness swelling value better than that of MDI resin. FTIR analysis on particleboard bonded by UF/MDI resin combination shows the presence of carbonyl group C=O vibration on multi substitution of urea at wave number of around 1,700 cm-1.

Modified methods of nanoparticles synthesis in pH-sensitive nano-carriers production for doxorubicin delivery on MCF-7 breast cancer cell line.

Purpose: Modified top-down procedure was successfully employed in the synthesis of aragonite nanoparticles (NPs) from cheaply available natural seawater cockle shells. This was with the aim of developing a pH-sensitive nano-carrier for effective delivery of doxorubicin (DOX) on MCF-7 breast cancer cell line.Methods: The shells were cleaned with banana pelts, ground using a mortar and pestle, and stirred vigorously on a rotary pulverizing blending machine in dodecyl dimethyl betane solution. This simple procedure avoids the use of stringent temperatures and unsafe chemicals associated with NP production. The synthesized NPs were loaded with DOX to form DOX-NPs. The free and DOX-loaded NPs were characterized for physicochemical properties using field emission scanning electron microscopy, transmission electron microscopy, zeta potential analysis, Fourier transform infrared spectroscopy, and X-ray diffraction. The release profile, cytotoxicity, and cell uptake were evaluated.Results: NPs had an average diameter of 35.50 nm, 19.3% loading content, 97% encapsulation efficiency, and a surface potential and intensity of 19.1±3.9 mV and 100%, respectively. A slow and sustained pH-specific controlled discharge profile of DOX from DOX-NPs was observed, clearly showing apoptosis/necrosis induced by DOX-NPs through endocytosis. The DOX-NPs had IC50 values 1.829, 0.902, and 1.0377 µg/mL at 24, 48, and 72 hrs, while those of DOX alone were 0.475, 0.2483, and 0.0723 µg/mL, respectively. However, even at higher concentration, no apparent toxicity was observed with the NPs, revealing their compatibility with MCF-7 cells with a viability of 92%.Conclusions: The modified method of NPs synthesis suggests the tremendous potential of the NPs as pH-sensitive nano-carriers in cancer management because of their pH targeting ability toward cancerous cells.

Synthesis, thermal, dielectric, and microwave reflection loss properties of nickel oxide filler with natural fiber‐reinforced polymer composite

ABSTRACTFabrication of hybrid composite of nickel oxide (NiO) combined with oil palm empty fruit bunch (OPEFB) reinforced with polycaprolactone (PCL) has been done by using thermal Haake blending machine, which ensured mixture homogeneity. All hybrid composites' characterizations were carried out using X‐ray diffraction (XRD), Fourier transform infrared spectrometry, differential thermogravimetry, thermogravimetric analysis, and scanning electron microscopy. The results showed that the XRD profile patterns of the composites clearly changed as the filler loading amount was increased. Fourier transform infrared spectra illustrated a slight change in the frequencies and positions of the peaks after adding NiO, indicating that some interactions occurred between C=O and O–H or among the fiber, NiO, and PCL. The microwave electromagnetic properties, such as reflection loss (dB), relative complex permittivity (εr =–j), and permeability (−j) were calculated at various microwave frequencies in the X‐band (8–12 GHz) range. It was observed that the thermal stability, magnetic, and dielectric properties of NiO:OPEFB:PCL composites were modified significantly with NiO addition. This enables the new hybrid composites to be used as engineering materials in the microwave applications. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019, 136, 46998.

Engine performance of biodiesel-biodiesel blends at varying engine speeds

Biodiesel blends with petroleum diesel have long been experimented on and considered good alternatives to petroleum diesel. Most blends considered biodiesel percentages of 20 and less. This work considered blending B100 of separate biodiesel feedstocks to determine their influence on improving physiochemical properties and engine performance. Palm kernel oil methyl ester (PKOME), Jatropha curcas methyl ester (JCME) and coconut oil methyl ester (COME) were blended with the help of a blending machine at 4000 rpm and run in a VW diesel engine to determine their effect on each other in terms of emissions and engine performance. PKOME & COME were blended in proportions of 100%, 75%, 50% and 25% to determine the best blend for optimum physiochemical properties and engine performance. JCME was also blended with COME in the same proportions. Ten separate test fuels of biodiesel and biodiesel-biodiesel blends were run at engine speeds between 800 rpm to 1 800 rpm to determine influence on engine performance and emissions. In terms of exhaust emissions and fuel consumption, the optimum values were obtained with 75% COME and 25% PKOME with brake-specific energy consumption (BSEC) of 15.4 MJ/kWh, CO (0.39 Vol. %), HC (45 ppm) and NOx (146 ppm). The optimum blend of JCME and COME was in the proportion of 75% JCME and 25% COME with BSEC of 13 MJ/kWh and CO, HC and NOx emissions of 0.24 Vol. %, 65 ppm and 256 ppm respectively. The results show that blending biodiesel of different feedstock can improve CIDI engine performance and exhaust emissions.

Evaluation of the Thermal Stabilization Effect of Maleic Anhydride Derivatives on Polyvinyl Chloride

Here, we synthesized a series of polymeric thermal stabilizers for polyvinyl chloride (PVC) based on maleic anhydride derivatives, including N-phenylmaleimide (NPMI), N-p-chlorophenyl maleimide (NCIPMI), N-p-nitrophenyl maleimide (NNOPMI), dibutyltin maleate (DBTM) and dioctyltin maleate (DOTM). Five specimens were prepared by mixing and rolling through a blending machine and a double-roller mixer, respectively. These samples were first subjected to thermal degradation in a 180°C hot oven, and fractions were collected every 10 min, followed by spotting on a slip of test paper. From the degree of color change in the test paper, the influences of these compounds on the thermal stability of PVC were estimated and such mechanisms were also discussed.

Manufacturing Design of the Novel Multi-Layer Blending Machine

In this study, a multi-layer blending machine was designed to mix cotton evenly. Being put inside via the feeding port, cotton was spread evenly by the oscillator which moves from left to right back and forth successively. Subsequently, cotton was stored as the multi-layer fibrous cotton in the rear reserve tank. Delivered by the first and the second conveyer belt, the fibrous cotton was sent to the front storage chamber to be cut by a lattice which pulled and dragged the marching cotton vertically. Finally, the processed cotton was rolled out by a striper roller, falling at a certain spot as scheduled, after which spread and blended evenly and thoroughly.

Control System Design for a Continuous Gravimetric Blender

AbstractIn this work the control system for a continuous gravimetric blender for polymer extrusion process has been designed. The plant considered in this paper is a blending machine that mixes two different polymers, a bulk one and an additive. Each component of the mix is metered by a dedicated screw meter system. The mass delivered by each meter is measured by a load cell. The two components are poured into a hopper (the mixer) directly embedded on the extruder input. The control objectives are manifold and include: accurate mass flow estimate on the basis of the weight and screw speed measurements; accurate mass flow regulation of each meter; keeping of the relative proportions among all the components that are metered in all the operating conditions; guarantee that inside the mixer there is always material enough to fulfill the mass flow variation request of the extruder.

A New Uncertainty Reduction Method for Fuel Fabrication Process with Erbia-Bearing Fuel

A new uncertainty reduction method is proposed to evaluate the prediction accuracy of neutronics characteristics by combining the generalized bias factor method and the cross section adjustment method. The present method is applied to a fuel fabrication process with erbia-bearing fuel. The cross section uncertainty of erbium is improved by means of cross section adjustment using experimental data of the erbia worths. For a blending machine (H/U = 0) used in the fuel fabrication process, the uncertainty reduction, which shows the rate of reduction of uncertainty, of the keff is 0.604 for the present method and 0.555 for the conventional bias factor method. Thus, the prediction uncertainties are reduced by the present method compared with by the bias factor method.

A New Uncertainty Reduction Method for Fuel Fabrication Process with Erbia-Bearing Fuel

A new uncertainty reduction method is proposed to evaluate the prediction accuracy of neutronics characteristics by combining the generalized bias factor method and the cross section adjustment method. The present method is applied to a fuel fabrication process with erbia-bearing fuel. The cross section uncertainty of erbium is improved by means of cross section adjustment using experimental data of the erbia worths. For a blending machine (H/U = 0) used in the fuel fabrication process, the uncertainty reduction, which shows the rate of reduction of uncertainty, of the keff is 0.604 for the present method and 0.555 for the conventional bias factor method. Thus, the prediction uncertainties are reduced by the present method compared with by the bias factor method.

Preparation of Biomaterials Composite with Mechanically Coated Particles

New preparation routes have been investigated for enhancing mechanical properties of a biomaterial composite consisting of with high-density polyethylene (HDPE) reinforced with hydroxyapatite (HA). HA was used as fine particles to coat each coarse particle of HDPE with an elliptical-rotor-type mixer and with a high-speed rotational impact blending machine. The effect of particle size of HDPE and mixing conditions were studied on mechanical properties of the composite material, such as rotor speed, total treatment time, number of preparation steps and total volume fraction of HA. In comparison, it was found that the embedment besides uniform coating and dispersion of HA fine particles onto the surface of HDPE core particle was easily achieved by rotational impact blending, due to high impact energy. This yielded relatively high properties. However, multi-coating steps or layers were required due to a high percentage of powder loss during operation. In contrast, uniform and tight coating of core particles was performed without particle loss by elliptical-rotor-type mixing. Nevertheless, due to a slight embedment of fine particles by gentle shear and compressive stress, HA could not disperse uniformly due to aggregates generated by the molten HDPE of core particles escaped through the thick and loose coating layer during material formation. This resulted in a weak bonding among coated particles to yield lower mechanical properties.

New Stationary Card Holder for the Mechanical Blending Machine

New Stationary Card Holder for the Mechanical Blending Machine