The partition of elastic strain energy in solid foams and lattice structures

Rapid advances in additive manufacturing techniques promise that, in the near future, the fabrication of functional cellular structures will be achieved with the desired cellular microstructures tailored to specific applications. It is therefore essential to develop a detailed understanding of the relationship between macroscopic mechanical response and cellular microstructure. The present study reports on the results of a series of computational experiments that explore the effect of topology and microstructural irregularity (or non-periodicity) on deformation modes of cellular structures under both uniaxial and biaxial stress states. A simple quantitative technique based on the partition of elastic strain energy into bending and stretch components is used to identify the distribution of deformation modes at a microstructural level. The relationship between nodal connectivity, morphological regularity and deformation modes is then explored through their influence on biaxial yield surfaces as obtained from finite element analyses.     

Automatically identifying changes that impact code-to-design traceability during evolution

An approach is presented that automatically determines if a given source code change impacts the design (i.e., UML class diagram) of the system. This allows code-to-design traceability to be consistently maintained as the source code evolves. The approach uses lightweight analysis and syntactic differencing of the source code changes to determine if the change alters the class diagram in the context of abstract design. The intent is to support both the simultaneous updating of design documents with code changes and bringing old design documents up to date with current code given the change history. An efficient tool was developed to support the approach and is applied to an open source system. The results are evaluated and compared against manual inspection by human experts. The tool performs better than (error prone) manual inspection. The developed approach and tool were used to empirically investigate and understand how changes to source code (i.e., commits) break code-to-design traceability during evolution and the benefits from such understanding. Commits are categorized as design impact or no impact. The commits of four open source projects over 3-year time durations are extracted and analyzed. The results of the study show that most of the code changes do not impact the design and these commits have a smaller number of changed files and changed less lines compared to commits with design impact. The results also show that most bug fixes do not impact design.     

Shape Memory Polyurethane as a Drilling Fluid Lost Circulation Material

Drilling fluid loss is a major problem with serious economic and environmental consequences. The use of traditional lost circulation materials (LCMs) to seal wide fractures increases the risk of bit nozzle plugging. In this work, smart LCMs based on shape memory polyurethane (SMPU) are proposed for the first time. SMPU can be programmed to recover at temperatures suited to a given well. As such, SMPU smoothly passes through the bit nozzles, while effectively seal wide fractures once activated. The SMPU is prepared by two step pre-polymerization and characterized by Fourier transform infrared spectra, X-ray diffraction, and differential scanning calorimeter. The SMPU is programmed by changing and fixing the original shape to a temporary shape through a thermo-mechanical process. The shape memory behavior of SMPU is analyzed by tensile apparatus. Compatibility of SMPU with WBMs is determined from mud rheology and filtration tests. Fracture sealing efficiency and shape recovery of SMPU are evaluated by a modified particle permeability apparatus fitted with a model fracture. The results confirm high sealing and shape recovery attributes of SMPU. The plug formed at 114 kg m^–3 SMPU and 80 °C experiences a sealing pressure of 100 bar with 71.5 cm³ cumulative fluid loss.     

Eco-Storage: A Hybrid Storage System with Energy-Efficient Informed Prefetching

In this paper, we present an energy-aware informed prefetching technique called Eco-Storage that makes use of the application-disclosed access patterns to group the informed prefetching process in a hybrid storage system (e.g., hard disk drive and solid state disks). Since the SSDs are more energy efficient than HDDs, aggressive prefetching for the data in the HDD level enables it to have as much standby time as possible in order to save power. In the Eco-Storage system, the application can still read its on-demand I/O reading requests from the hybrid storage system while the data blocks are prefetched in groups from HDD to SSD. We show that these two steps can be handled in parallel to decreases the system’s power consumption. Our Eco-Storage technique differs from existing energy-aware prefetching schemes in two ways. First, Eco-Storage is implemented in a hybrid storage system where the SDD level is more energy efficient. Second, it can group the informed prefetching process and quickly prefetch the data from the HDD to the SSD to increase the frequent HDD standby times. This will makes the application finds most of its on-demand I/O reading requests in the SSD level. Finally, we develop a simulator to evaluate our Eco-Storage system performance. Our results show that our Eco-Storage reduces the power consumption by at least 75 % when compared with the worst case of non-Eco-Storage case using a real-world I/O trace.