The present work expands the application of Puck and Schürmann Inter-Fiber Fracture criterion to fiber reinforced thermoplastic 3D-printed composite materials. The effect of the ratio between the transverse compressive strength and the in-plane shear strength is discussed and a new transition point between the fracture conditions under compressive loading is proposed. The recommended values of the inclination parameters, as well as their effects on the proposed method, are also discussed. Failure envelopes are presented for different 3D-printed materials and also for traditional composite materials. The failure envelopes obtained here are compared to those provided by the original Puck and Schürmann criterion and to those provided by Gu and Chen. The differences between them are analyzed with the support of geometrical techniques and also statistical tools. It is demonstrated that the Expanded Puck and Schürmann is capable of providing more suitable failure envelopes for fiber reinforced thermoplastic 3D-printed composite materials in addition to traditional semi-brittle, brittle and intrinsically brittle composite materials.

This study investigates the mechanical properties of thermoplastic polyurethane (TPU) 60A, which is a flexible material that can be used to produce soft robotic grippers using additive manufacturing. Tensile tests were conducted under ISO 37 and ISO 527 standards to assess the effects of different printing orientations (0°, 45°, −45°, 90°, and quasi-isotropic) and test speeds (2 mm/min, 20 mm/min, and 200 mm/min) on the material’s performance. While the printing orientations at 0° and quasi-isotropic provided similar performance, the quasi-isotropic orientation demonstrated the most balanced mechanical behavior, establishing it as the optimal choice for robust and predictable performance, particularly for computational simulations. TPU 60A’s flexibility further emphasizes its suitability for handling delicate objects in industrial and agricultural applications, where damage prevention is critical. Computational simulations using the finite element method were conducted. To verify the accuracy of the models, a comparison was made between the average stresses of the tensile test and the computational predictions. The relative errors of force and displacement are lower than 5%. So, the constitutive model can accurately represent the material’s mechanical behavior, making it suitable for computational simulations with this material. The analysis of strain rates provided valuable insights into optimizing production processes for enhanced mechanical strength. The study highlights the importance of tailored printing parameters to achieve mechanical uniformity, suggesting improvements such as biaxial testing and G-code optimization for variable thickness deposition. Overall, the research study offers comprehensive guidelines for future design and manufacturing techniques in soft robotics.

Companies worldwide have been investing in solutions to provide production and cost optimization. As a result, real-time operation systems have been used to help in achieving these objectives. This paper provides a description of the use of real-time operation systems and how the integration of their disciplines made it possible to optimize production and costs for oil and gas fields.Working as an integrated multi-disciplinary approach, real-time production-operation systems enable the maximization of oil and gas production of assets at lower costs, while providing a better understanding of the current scenario of oil and gas fields. To obtain these improvements, some characteristics to be considered are described below. The consolidation of the whole asset- production data into a single system provides mechanisms to monitor, analyze, and control oil and gas fields. These data are automatically uploaded to the system to minimize manual efforts, making more time available for process analyses. To avoid spurious data, an automatic validation mechanism for the data acquisition process was developed. In addition to production monitoring and the enhanced data quality, historical data, alarms, and statistic tools are used to improve the data analysis and interpretation process. The solution also enables the online well-production prediction using a neural-networks model as well as the integration with a reliable system to identify, quantify, and classify production losses. Because the information is displayed in an online system, the same data at the same time are available for access from different users.The use of real-time production-operation systems enables strategies for asset managers to make faster decisions and provide better solutions to asset operational issues.These outcomes are achieved as a result of integrated production, losses, and process-parameters information, as well as the acquisition process of validated data and the availability of tools for analysis and interpretation.

Currently, considering the rising concern in climate change, there is a clear necessity for technologies that can prolong the useful life of products through the ability to repair, re-manufacture and refurbish. As such, additive manufacturing has been a subject of research due to its design and resource consumption capabilities. However, there is a lack of more detailed information regarding environmental performances, especially in Directed Energy Deposition technology. The present paper presents a life-cycle assessment of the production and use of Directed Energy Deposition, making use of foreground data to build a life-cycle inventory and quantify the potential impacts. The equipment is analyzed for its refurbishment capabilities on an obsolete mold, and compared with the environmental impact of producing a new mold through conventional technology. The compiled inventory with detailed and primary information will enrich the current literature on this technology. The impact results show that the robot, deposition table and security cell are the most relevant subsystems for the system production impacts. In the refurbishment analysis, the refurbished mold part has lower impacts than the conventionally produced, thus showing that there is great potential in using additive manufacturing for circular economy loops.

The present work describes a methodology to compute equivalent volumes representing the microstructure of 3D-printed continuous fiber-reinforced thermoplastics, based on a statistical characterization of the fiber distribution. In contrast to recent work, the methodology herein presented determines the statistically equivalent fiber distribution directly from cross-section micrographs, instead of generating random fiber arrangements. For this purpose, several regions, with different sizes and from different locations, are cropped from main cross-section micrographs and different spatial descriptor functions are adopted to characterize the microstructures in terms of agglomeration and periodicity of the fibers. Detailed information about the adopted spatial descriptors and the algorithm implemented to identify the fiber distribution, as well as to define the location of cropped regions, are given. From the obtained statistical characterization results, the minimum size of the equivalent volume required to be representative of the fiber distribution, which is found in the cross-section micrographs of 3D-printed composite materials, is presented. To support the findings, as well as to demonstrate the effectiveness of the proposed methodology, the homogenized properties are also computed using representative equivalent volumes obtained in the statistical characterization and the results are compared to those experimentally measured, which are available in the literature.