This paper comparatively investigates the arc plasma morphology and the droplet transfer behavior and Characteristic of electrical signal between the pulsed MAG welding and the medium and low power ...laser assisted pulsed MAG hybrid Welding. Compared with the pulsed MAG welding, the assisted laser acts on the substrate before the arc to generate a stable keyhole and mass metallic vapor is generated near the keyhole leading the expansion of arc plasma morphology. The arc plasma appears obvious compression phenomenon under the action of medium power assisted laser. In addition, the keyhole has an attractive effect on the discharge channel and the height of the discharge channel becomes shorter, which makes the arc initiation stage more stable. The contact area between the arc root and the workpiece is expanded, in addition the laser has a compression effect on the arc, making the arc energy density higher and the energy use more efficient. The acting of assisted laser increased the droplet transfer frequency with the power increases, which essentially changes the electromagnetic force acting on the droplet. Others, the range of welding voltage distribution and the probability of high voltage distribution are reduced, and the transition is more stable.
•In-depth study of energy deposition in laser metal fusion with feedstock wire.•Effect of wire feed rate, beam and wire angular positions, beam-wire offset on energy deposition in the workpiece and ...in the wire.•Sources of instability causing metal transfer break up.
In this study, laser metal fusion with feedstock wire is addressed. We investigated how various process parameters affect the fraction of beam energy that is absorbed by the wire and the workpiece and the metal transfer from the feedstock wire to the melt pool. To perform this research, a thermo-fluid dynamic model with tracking of free surface deformation was developed to include the feeding of a solid wire and predict its melting. The fraction of beam energy absorbed by the metal was modeled as a function of local surface curvature and temperature, accounting for multiple Fresnel reflections and absorptions. The model was applied to Titanium alloy (Ti-6Al-4V) with a 1.07 μm laser and a process in conduction mode. Experiments at various wire feeding rates were conducted to evaluate the model’s ability to predict the process and a good agreement was obtained. The different parameters studied were the beam angular position, the wire angular position, the wire feed rate, and the beam-wire offset. The analysis of the simulation results gave a detailed physical understanding of the laser energy use. It highlighted that thermocapillary and Rayleigh-Plateau instabilities can contribute to the transition from continuous to drop metal transfer mode. Damping these instabilities might thus allow using a wider process window.
Aiming at the problem that the speed of the contact point of the multi-section pipeline robot changes abruptly during the turning process, which will affect the stability of the robot's motion, the ...turning process of the robot is explored. Based on the pose model in the pipe bend of the pipe robot, the position and velocity of the contact point between the robot and the pipe are solved. Firstly, the turning process of the robot is briefly described; secondly, the pose model of the pipeline robot in the pipe bend is established and the position of the contact point between the robot and the pipeline is solved; then the speed of the robot is analyzed to find the attitude angle where the speed of the robot does not change suddenly. Finally, the correctness of the conclusion and the solution process is verified by the Matlab numerical solution and Adams simulation, which lays a foundation for the continuous and stable control of robot turning process.
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•The co-digestion at the mixture 20 % OMWW: 80 % FW improved the process stability in terms of ALK, pH and VFA/ALK ratio.•The methane yield achieved the maximum of 302.16 mLSTP CH4. g ...VS−1 with the addition of 80 % FW.•The methane yield increased by 37 % with 20 % OMWW: 80 % FW compared to control.•The biodegradation rate enhanced by 56 % with 80 % FW.
The Olive oil industry is one of the most important agro-industrial sectors in the Mediterranean countries, in which Morocco is the world's 5th largest olive oil producer. By-products of this agro-industry such as OMWW and olive mill pomace represent a major challenge for the environment. The high concentration of polyphenols in OMWW and the lack of nitrogen make AD of this substrate difficult. AcoD of OMWW with other substrates is an alternative solution to fill this gap. In the present study, AcoD of OMWW with FW from the Ibn Tofail University campus restaurant was investigated, in order to enhance AD of OMWW in terms of methane production and process stability. Different co-substrates were prepared and tested, in which the content of OMWW varied from 20 to 80 %.The MY and biodegradability were optimal at the mixture 20 % OMWW: 80 % FW showing the values of 302.16 ± 3.04 mLSTP CH4.gVS−1 and 86.0 ± 4.1 % respectively. The process stability was investigated through the alkalinity and the volatile fatty acids ratio VFA/ALK, and the results show that all mixtures were stable except the control test mono AD of OMWW. This stability might be due to the simultaneous presence of ammonia ions from the decomposition of proteins contained in FW and bicarbonate ions. The OLR increased when the added loads increased throughout the conducted experiments. The OLR of the mixture 20 % OMWW: 80 % FW was 2.0 ± 0.1 kg VS. m-3.d−1) higher than OLR of control test (1.45 ± 0.05 kg VS.m-3.d−1). Furthermore, two kinetics models were applied (modified Gompertz model and the Logistic model). The results shown that both models had a good conformity, and the modified Gompertz model was the more appropriate showing a higher values of R2 than logistic model. Moreover, the lag time decreased when the OMWW proportion increased.
In this work, a comprehensive dynamic model of a moving grate Waste-to-Energy plant is developed using MATLAB Simulink. The objective is to develop a reliable and flexible model which can reproduce ...the dynamic behavior of combustion chamber and boiler. For this purpose, an extensive number of process data is used both in model development and for validation. Contrary to previous works in literature, fluctuations in both waste properties and operational set points are taken into account. The validated model is then used to study the dynamic response of the plant to changes in important process parameters. As expected, the dynamic response of the plant is faster for changes in primary and secondary air than for changes in grate speed and waste flow. The steam production response is from 1 to 4 min slower than the flue gas oxygen concentration response. Moreover, the response time depends to a large extent on the properties of the waste; as an example, an increase in waste humidity from 25% to 35% results in a 21 min increase in the steam production response time. Such characterization of the dynamic response of the plant is fundamental to develop improved control strategies.
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•A dynamic model of a moving grate Waste-to-Energy plant has been developed.•The effect of waste composition on the dynamic plant response is analysed.•Plant response was slower for higher moisture and ash content in the waste.
Anaerobic digestion, a virtuous process to reduce and reuse biowaste to obtain renewable bioenergy, is often dramatically subject to process failure during long timescale operation. This study aimed ...to evaluate the process robustness and reliability by elucidating the composition of microbial populations and the link with process parameters under a wide range of different operating conditions in long-term semicontinuous reactors. Mesophilic semipilot digesters were fed with real urban biowaste, namely, food waste alone or food waste with activated sludge, to explore the impact of feedstock composition and organic loading rate (OLR: 0.8–3.5 kgVSfed m−3d−1) on volatile fatty acid (VFA) composition and pattern, biomethane production, and core microbiome dynamics. The major bacterial phyla were Bacteroidetes (basically more abundant when the feedstock was only food waste), followed by Chloroflexi and Firmicutes, while Euryarcheota hydrogenotrophic methanogens, mainly represented by members of the Methanomicrobiales family, prevailed in all systems. During monodigestion of food waste, however, independent of the OLR, methanogenic conversion of fermentative end-products decreased progressively after 1 HRT. In particular, the observed propionate and butyrate accumulations seemed to derive from thermodynamic limitations due to the increase in hydrogen levels, indicative of progressively lower H2 consumption rates. However, the induced process recovery assured a large degradation of fatty acids with higher carbon chain lengths together with methane production, suggesting the upswing of hydrogenotrophic methanogen activity emerging after stressful conditions. The addition of a minimal amount of sludge boosted the methane production rates (up to 0.29 ± 0.1 Nm3CH4 kg−1VSfed) along with excellent process stability, also at a high OLR, creating a robust methanogen community shaped by high biodiversity. Methanospirillum and Candidatus Methanofastidiosum, strictly related to the codigestion systems, have a large H2 consumption capacity, thus preventing thermodynamic bottlenecks and process failure.
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Lyophilization formulation and process development for lipophilic nanoparticle (NPs) products is highly challenging as the NPs have a low colloidal stability. We compared two ...different NP types, pure paliperidone palmitate nanocrystals and trimyristin solid lipid nanoparticles regarding formulation, process, and storage stability aspects. Freeze-thaw studies were conducted to investigate the basic formulation aspects such as buffer type, pH, and ionic strength as well as different cryoprotectants. In freeze-drying conventional ramp freezing was performed and compared to freezing with an annealing step added or with controlled ice nucleation. Different formulations were lyophilized and tested for short-term storage stability up to 6 weeks. Samples were analyzed for particle size, subvisible particle number, specific surface area, residual moisture, crystallinity, and glass transition temperature. Sucrose significantly better stabilized both NP types against freeze-thaw stress compared to mannitol demonstrating the importance of a fully amorphous matrix. While the impact of buffer type and pH was negligible, the aggregation propensity of NPs was reduced in presence of NaCl. The freezing step also impacted NP aggregation but the effect was less important than the formulation design. Surfactants did not necessarily improve the colloidal stability but resulted in a lower glass transition temperature of the lyophilizates and may cause phase separation which limits storage stability. This hurdle can be overcome by using a hydroxypropyl–β–cyclodextrin/ sucrose mixture as cryoprotectant. In general, we could show a similar freeze–drying behavior of the two NP types. Thus, we established a formulation and process approach to achieve stable lyophilizates of lipophilic NPs based on two different types of NPs. The general rules should be transferable to other NPs facilitating lyophilization development.
Wire arc additive manufacturing (WAAM) technology was adopted to deposite 2Cr13 thin-wall part using robotic cold metal transfer (CMT) equipment; the process stability, phase identification, ...microstructural evolution, and tensile properties in different layers were investigated. The results showed that a smooth surface was obtained for each layer due to the stable droplet transfer process, which ensured a stable deposition process. Positions in different layers had no significant influence on the structural aspects of the as-fabricated part according to XRD results. Elongated ferrite grains and fine-grained acicular martensite within the matrix in the top layer were recrystallized, instead of a spatial periodicity of martensite laths within equiaxed ferrite grains in the inner layers. Martensite content was increased gradually away from the base metal in the 05–25 th layers except nearly 100% martensite in the first layer. Long axis of martensite laths was randomly distributed in the X-Y plane in the both top and middle regions, while an epitaxial growth parallel to the building direction was found in the X-Z and Y-Z planes. Higher homogeneous ultimate tensile strength (UTS) and strong anisotropy in poorer ductility were obtained for the AM part when compared with the as-solutioned counterpart. Fracture behavior was transformed from ductile to mixed-mode, and finally to brittle from the 01 st layer to the 25 th layer.
•2Cr13 thin-wall part fabricated using robotic CMT technology.•A stable metal droplet transfer process during one cycle.•Microstructural evaluation using XRD, OM, and EBSD.•A spatial periodicity of microstructures within the part.•Enhanced homogeneous UTS and poor anisotropic ductility.
Reliable quality control of resistance spot welding (RSW) is a long-standing challenge, due to random disturbance on automotive production lines. In this paper, a quality evaluation framework is ...proposed based on dynamic resistance (DR) signals, aiming to accurately predict welding quality. The proposed framework integrates welding process stability with deep learning models. Given the uniform variation pattern of each weld with the same schedule, process stability can be determined based on the reference curve constructed by the low-rank and sparse decomposition method. Subsequently, a one-dimensional convolutional neural network (1DCNN) with channel attention mechanism is developed to further predict welding quality, which can perform channel-wise feature recalibration to enhance the classification performance. Extensive experiments substantiate that the proposed network yields a remarkable classification performance compared with typical algorithms on several RSW datasets collected on an actual production line. This study provides a valuable reference to achieve an intelligent online quality inspection system in the automotive manufacturing industry.
•A framework combining process stability with deep learning for resistance spot welding quality inspection is presented.•Low-rank and sparse decomposition method is used to construct reference curves to determine the process stability.•A deep network performs channel-wise feature recalibration to enhance the classification performance.•The model effectiveness is experimentally validated via performance comparison.
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