This work explores a spatial printing method to fabricate continuous fiber-reinforced thermoplastic composites (CFRTPCs), which can achieve exceptional mechanical performance. For models giving complex 3D stress distribution under loads, typical planar-layer based fiber placement usually fails to provide sufficient reinforcement due to their orientations being constrained to planes. The effectiveness of fiber reinforcement could be maximized by using multi-axis additive manufacturing (MAAM) to better control the orientation of continuous fibers in 3D-printed composites. Here, we propose a computational approach to generate 3D toolpaths that satisfy two major reinforcement objectives: (1) following the maximal stress directions in critical regions and (2) connecting multiple load-bearing regions by continuous fibers. Principal stress lines are first extracted in an input solid model to identify critical regions. Curved layers aligned with maximal stresses in these critical regions are generated by computing an optimized scalar field and extracting its iso-surfaces. Then, topological analysis and operations are applied to each curved layer to generate a computational domain that preserves fiber continuity between load-bearing regions. Lastly, continuous fiber toolpaths aligned with maximal stresses are generated on each surface layer by computing an optimized scalar field and extracting its iso-curves. A hardware system with dual robotic arms is employed to conduct the physical MAAM tasks depositing polymer or fiber reinforced polymer composite materials by applying a force normal to the extrusion plane to aid consolidation. When comparing to planar-layer based printing results in tension, up to 644% failure load and 240% stiffness are observed on shapes fabricated by our spatial printing method. We demonstrate the versatility of our approach through various complex load cases which demonstrate their successful implementation of continuous fiber printing in 3D.

The effect of thermal aging of homogenized Fe-Au and Fe-Au-W alloys, irradiated at room temperature with hydrogen ions, was studied for an aging treatment at 300 °C for aging times up to 100 h. The aging behavior of the Fe-based alloys is compared to the results for pure Fe. The precipitation behavior of Au-rich and W-rich precipitates and its correlation to the H⁺ irradiation-induced defects is investigated by variable energy positron annihilation spectroscopy (VEPAS). The formation of open-volume defects after irradiation is monitored by an increase in the S parameter, while the recovery of the vacancy-like defects and the formation of precipitates are signalled by an increase in the W parameter. Au-rich precipitation continuously develops during long-term aging, as indicated by the increase in the W parameter. The change of the W parameter in the Fe-Au-W alloy is not only due to the effect of solute W on the Au precipitates, but also because of the interface of W-rich Laves phase with matrix.

Hydrocarbon reservoir models have a high degree of uncertainty regarding their reservoir geometry and structure. A range of conceptual models should therefore be generated to explore how first-order uncertainties impact fluids-in-place, reservoir dynamics, and development decisions. However, it is very time consuming to generate and explore a large number of conceptual models using conventional reservoir modelling and simulation workflows. Key reservoir concepts are therefore often locked in early and are difficult to change later. To overcome this challenge, the Rapid Reservoir Modelling (RRM) software has been developed to prototype reservoir models across scales and test their dynamic behaviour. RRM complements existing workflows in that conceptual models can be prototyped, explored, compared, and ranked rapidly prior to detailed reservoir modelling. Reservoir geology is sketched in 2D with geological operators and translated in real-time into geologically correct 3D models. Flow diagnostics provide quantitative information for these reservoir model prototypes about their static and dynamic behaviours. Numerical well testing (NWT) is implemented to further interrogate the reservoir model. The combination of surface-based reservoir modelling with geological operators, flow diagnostics and NWT on unstructured grids enable, for the first time rapid prototyping of reservoir geologies with real-time feedback on fluid flow behaviour.

Constructing or refining complex reservoir models at the appraisal, development, or production stage is a challenging and time-consuming task that entails a high degree of uncertainty. The challenge is significantly increased by the lack of modeling, simulation and visualization tools that allow prototyping of reservoir models and development concepts, and which are simple and intuitive to use. Conventional modeling workflows, facilitated by commercially available software packages, have remained essentially unchanged for the past decade. However, these are slow, often requiring many months from initial model concepts to flow simulation or other outputs; moreover, many model concepts, such as large scale reservoir architecture, become fixed early in the process and are difficult to retrospectively change. Such workflows are poorly suited to rapid prototyping of a range of reservoir model concepts, well trajectories and development options, and testing of how these might impact on reservoir behavior. We present a new reservoir modeling and simulation approach termed Rapid Reservoir Modeling (RRM) that allows such prototyping and complements existing workflows. In RRM, reservoir geometries that describe geologic heterogeneities (e.g. faults, stratigraphic, sedimentologic and/or diagenetic features) are modelled as discrete volumes bounded by surfaces, without reference to a predefined grid. These surfaces, and also well trajectories, are created and modified using intuitive, interactive techniques from computer visualization, such as Sketch Based Interfaces and Modeling (SBIM). Input data can be sourced from seismic, geocellular or flow simulation models, outcrop analogues, conceptual model libraries or blank screen. RRM outputs can be exported to conventional workflows at any stage. Gridding or meshing of the models within the RRM framework allows rapid calculation of key reservoir properties and dynamic behaviors linked with well trajectories and development plans. We demonstrate here a prototype of the RRM workflow using a number of examples. The work is significant because it allows, for the first time, application of rapid prototyping methods in reservoir modeling and simulation. Such methods are widely used in other fields of engineering design and allow improved scoping of concepts and options prior, or in addition, to detailed modeling. Moreover, SBIM can be used on a range of hardware architectures, including table tops and surface PCs, fostering collaboration within integrated asset teams.