Quasi Static and Fatigue Properties of Long Carbon Fiber Reinforced Polyamide

In this experimental work, the quasi static and fatigue properties of a 40 wt.% long carbon fiber reinforced partially aromatic polyamide (Grivory GCL-4H) were investigated. For this purpose, microstructural parameter variations in the form of different thicknesses and different removal directions from injection-molded plates were evaluated. Mechanical properties decreased by increasing misalignment away from the melt flow direction. By changing the specimen thickness, no change in the general fiber distribution pattern transversal and normal to the axis of melt flow was observed. It has shown that with increasing specimen thickness the quasi static properties along the melt flow direction decreased and vice versa resulting in superior properties normal to the melt flow axis. At around 5 mm, an intersection suggests quasi-isotropic behavior. In addition, the fatigue strength of the material was significantly higher in the flow direction than normal to the flow direction. No change in fatigue life was observed while changing specimen thickness. The Basquin equation seems to describe the effect of stress amplitude on the fatigue strength of this composite. Scanning electron microscopy was used to investigate fracture surfaces of tested specimens. Results show that mechanical properties and morphological structures depend highly on fiber orientation.

Evaluating Infill Well Performance and Fracture Driven Interactions Using Intervention Based Distributed Fiber Optics

Distributed Fiber Optics (DFO) technology has been the new face for unconventional well diagnostics. This technology focuses on measuring Distributed Acoustic Sensing (DAS) and Distrusted Temperature Sensing (DTS) to give an in-depth understanding of well productivity pre and post stimulation. Many different completion design strategies, both on surface and downhole, are used to obtain the best fracture network outcome; however, with complex geological features, different fracture designs, and fracture driven interactions (FDIs) effecting nearby wells, it is difficult to grasp a full understanding on completion design performance for each well. Validating completion designs and improving on the learnings found in each data set should be the foundation in developing each field. Capturing a data set with strong evidence of what works and what doesn't, can help the operator make better engineering decisions to make more efficient wells as well as help gauge the spacing between each well. The focus of this paper will be on a few case studies in the Bakken which vividly show how infill wells greatly interfered with production output. A DFO deployed with a 0.6" OD, 23,000-foot-long carbon fiber rod to acquire DAS and DTS for post frac flow, completion, and interference evaluation. This paper will dive into the DFO measurements taken post frac to further explain what effects are seen on completion designs caused by interferences with infill wells; the learnings taken from the DFO post frac were applied to further escalate the understanding and awareness of how infill wells will preform on future pad sites. A showcase of three separate data sets from the Bakken will identify how effective DFO technology can be in evaluating and making informed decisions on future frac completions. In this paper we will also show and discuss how DFO can measure real time FDI events and what measures can be taken to lessen the impact on negative interference caused by infill wells.

Simulating the Trajectory and Biomass Growth of Free-Floating Macroalgal Cultivation Platforms along the U.S. West Coast

Trajectory tracking and macroalgal growth models were coupled to support a novel macroalgae-harvesting concept known as the Nautical Off-shore Macroalgal Autonomous Device (NOMAD). The NOMAD consists of 5 km long carbon-fiber longlines that are seeded and free float southward along the U.S. West Coast for approximately 3 months before harvesting off the California coast, taking advantage of favorable environmental conditions. The trajectory and macroalgal growth models were applied to answer planning questions pertinent to the techno-economic analysis such as identifying the preferred release location, approximate pathway, timing until harvest, and estimated growth. Trajectories were determined with the General NOAA Operational Modeling Environment (GNOME) model, using 11 years of current and wind data, determining probabilities by running nearly 40,000 Monte Carlo simulations varying the start time and location. An accompanying macroalgal growth model was used to estimate the growth of macroalgae based on the trajectory tracks and environmental forcing products, including light, temperature and nutrients. Model results show that NOMAD lines transit south in the months of April to September due to seasonal currents, taking approximately 3 months to reach Southern California. During transit, NOMAD lines are dispersed but typically avoid beaching or passing through marine sanctuaries. NOMAD lines can yield up to 30 kg wet weight per meter of cultivation line.

The fabrication of long carbon fiber reinforced polylactic acid composites via fused deposition modelling: Experimental analysis and machine learning

As a promising technology to revolutionize traditional manufacturing processes, additive manufacturing has received great attention by virtue of its cost savings, minimum material waste, and tool-less production of complex geometries. The development of fiber-reinforced composites via this technique that exhibits superior strength is thus becoming a hot spot in recent years. This paper focused on the 3 D printing of polylactic acid (PLA) composites with the incorporation of chopped long carbon fiber (CF) with an average length of 4.6 mm via FDM fabrication. By varying its loading quantity, the effect of CF contents on the mechanical, thermal, and morphological properties of these 3 D printed composites was thoroughly investigated. The results showed that with the increase of CF contents, all assessed properties of CF/PLA composites including tensile properties, flexural properties, hardness, and thermal conductivity were effectively improved compared to the neat PLA. Their performance exhibited the same upward-downward-upward trend with the addition of CF. It can be attributed to the mutual influence generated from inter-/intra filament porosities and the high stiffness of CF. Meanwhile, a machine learning technique, Gaussian Process modeling was also introduced in this study for the property prediction of the composites. In comparison with the experimental analysis, the optimal CF content of 6.7 wt% with the best overall performance was predicted using this model, which was very close to the best experimental results at 5 wt% CF.

Evaluation of mechanical properties and EMI shielding effectiveness of long carbon fiber reinforced thermoplastic with different matrix

In the present study, the difference of long carbon fiber reinforced thermoplastic (C-LFT) depending on the type of polymer resins at the same carbon fiber content (30 wt.%) was compared. The different types of C-LFT were made using five polymer resins such as polyamide 6, polyamide 6,6, polycarbonate, high density polyethylene and polypropylene. Tensile test, flexural test, and unnotched Izod impact test were carried out and the cause of difference in the mechanical properties was considered by analyzing the adhesion characteristics. Fracture appearance and work of adhesion between the fiber and the resin were observed. In addition, the difference and its cause in electromagnetic interference shielding effectiveness (EMI SE) was investigated. From the results, the polyamide 6 is most appropriate to the carbon fiber among the samples in the aspects of interfacial shear strength and fiber dispersion.