8,596 research outputs found
Effects of microstructure architecture on the fracture of fibrous materials
Fibrous materials is one of the potential scaffolds used for tissue engineered constructs. One of prerequisite properties for tissue engineered construct is fracture property. The work here study the relationship between microstructure architecture and fracture behavior of fibrous networks by using finite element analysis. The result shows that fibrous networks are toughened by either reducing the fiber density or cross-link percentage of networks. Such implementation increases the degree of non-affine deformation and produces a more compliant response at the crack-tip region. The non-affine deformation in fibrous networks involves fiber movement like fiber rearrangement and reorientation, where such mechanisms allow stress delocalization to occur at the crack-tip region and results in a better fracture toughness of fibrous networks. The findings form this work provide the design guideline of fibrous materials with enhanced toughness for multiple applications
Fracture Toughness of Fibrous Membranes
Random fibrous networks exist in both natural biological and engineering materials. While the nonlinear deformation of fibrous networks has been extensively studied, the understanding of their fracture behaviour is still incomplete. To study the fracture toughness of fibrous materials, the near-tip region is crucial because failure mechanisms such as fibril rupture occur in this region. The consideration of this region in fracture studies is, however, a difficult task because it involves microscopic mechanical responses at a small length scale. This paper extends our previous finite element analysis by incorporating the microscopic responses into a macroscopic domain by using a submodeling technique. The detailed study of microstructures at crack tips show a stochastic toughness of membranes due to the random nature of fibrous networks. Further, the sizes of crack tip region, which are sufficient to provide a reasonable prediction of fracture behaviour in a specific type of fibrous network, were presented. Future work includes improving the current linear assumption in the macroscopic models to become nonlinear
Extremely high room-temperature two-dimensional hole gas mobility in Ge/Si0.33Ge0.67/Si(001) p-type modulation-doped heterostructures
To extract the room-temperature drift mobility and sheet carrier density of two-dimensional hole gas (2DHG) that form in Ge strained channels of various thicknesses in Ge/Si0.33Ge0.67/Si(001) p-type modulation-doped heterostructures, the magnetic field dependences of the magnetoresistance and Hall resistance at temperature of 295 K were measured and the technique of maximum entropy mobility spectrum analysis was applied. This technique allows a unique determination of mobility and sheet carrier density of each group of carriers present in parallel conducting multilayers semiconductor heterostructures. Extremely high room-temperature drift mobility (at sheet carrier density) of 2DHG 2940 cm2 V–1 s–1 (5.11×1011 cm–2) was obtained in a sample with a 20 nm thick Ge strained channel
Toughening in electrospun fibrous scaffolds
Electrospun scaffolds mimic the microstructure of structural collagenous tissues and have been widely used in tissue engineering applications. Both brittle cracking and ductile failure have been observed in scaffolds with similarly random fibrous morphology. Finite element analysis can be used to qualitatively examine the mechanics of these differing failure mechanisms. The finite element modeling demonstrates that the noncontinuum deformation of the network structure results in fiber bundle formation and material toughening. Such toughening is accommodated by varying fiber properties, including allowing large failure strains and progressive damage of the fibers.The authors acknowledge the support from the Ministry of Higher Education Malaysia, Khaow
Tonsomboon, Daniel Strange, and Anne Bahnweg.This is the final published version. It first appeared at http://scitation.aip.org/content/aip/journal/aplmater/3/1/10.1063/1.4901450
Hole density dependence of effective mass, mobility and transport time in strained Ge channel modulation-doped heterostructures
We performed systematic low-temperature (T = 350 mK–15 K) magnetotransport measurements on the two-dimensional hole gas with various sheet carrier densities Ps = (0.57–2.1)×1012 cm–2 formed in the strained Ge channel modulation-doped (MOD) SiGe heterostructures grown on Si substrates. It was found that the effective hole mass deduced by temperature dependent Shubnikov–de Hass oscillations increased monotonically from (0.087±0.05)m0 to (0.19±0.01)m0 with the increase of Ps, showing large band nonparabolicity in strained Ge. In contrast to this result, the increase of the mobility with increasing Ps (up to 29 000 cm2/V s) was observed, suggesting that Coulomb scattering played a dominant role in the transport of the Ge channel at low temperatures. In addition, the Dingle ratio of the transport time to the quantum lifetime was found to increase with increasing Ps, which was attributed to the increase of remote impurity scattering with the increase of the doping concentration in MOD SiGe layers
Inward Leakage in Tight-Fitting PAPRs
A combination of local flow measurement techniques and fog flow visualization was used to determine the inward leakage for two tight-fitting powered air-purifying respirators (PAPRs), the 3M Breathe-Easy PAPR and the SE 400 breathing demand PAPR. The PAPRs were mounted on a breathing machine head form, and flows were measured from the blower and into the breathing machine. Both respirators leaked a little at the beginning of inhalation, probably through their exhalation valves. In both cases, the leakage was not enough for fog to appear at the mouth of the head form
Developing and applying a user-centered model for the design and implementation of information visualization tools
The objective of this paper is to show how approaches for user-centered information visualization design and development are being applied in the context of healthcare where users are not familiar with information visualization techniques. We base our design methods on user-centered frameworks in which 'prototyping' plays an important role in the process. We modify existing approaches to involve prototyping at an early stage of the process as the problem domain is assessed. We believe this to be essential, as it increases users' awareness of what information visualization techniques can offer them and that it enables users to participate more effectively in later stages of the design and development process. This also acts as a stimulus for engagement. The problem domain analysis stage of a pilot study using this approach is presented, in which techniques are being collaboratively developed with domain users from a healthcare institution. Our results suggest that this approach has engaged users, who are subsequently able to apply generic information visualization concepts to their domains and as a result are better equipped to take part in the subsequent collaborative design and development process
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Review: Consumption-stage food waste reduction interventions - What works and how to design better interventions
Food waste prevention has become an issue of international concern, with Sustainable Development Goal 12.3 aiming to halve per capita global food waste at the retail and consumer levels by 2030. However there is no review that has considered the effectiveness of interventions aimed at preventing food waste in the consumption stages of the food system. This significant gap, if filled, could help support those working to reduce food waste in the developed world, providing knowledge of what interventions are specifically effective at preventing food waste.
This paper fills this gap, identifying and summarizing food-waste prevention interventions at the consumption/consumer stage of the supply chain via a rapid review of global academic literature from 2006 to 2017.
We identify 17 applied interventions that claim to have achieved food waste reductions. Of these, 13 quantified food waste reductions. Interventions that changed the size or type of plates were shown to be effective (up to 57% food waste reduction) in hospitality environments. Changing nutritional guidelines in schools were reported to reduce vegetable waste by up to 28%, indicating that healthy diets can be part of food waste reduction strategies. Information campaigns were also shown to be effective with up to 28% food waste reduction in a small sample size intervention.
Cooking classes, fridge cameras, food sharing apps, advertising and information sharing were all reported as being effective but with little or no robust evidence provided. This is worrying as all these methods are now being proposed as approaches to reduce food waste and, except for a few studies, there is no reproducible quantified evidence to assure credibility or success. To strengthen current results, a greater number of longitudinal and larger sample size intervention studies are required. To inform future intervention studies, this paper proposes a standardised guideline, which consists of: (1) intervention design; (2) monitoring and measurement; (3) moderation and mediation; (4) reporting; (5) systemic effects.
Given the importance of food-waste reduction, the findings of this review highlight a significant evidence gap, meaning that it is difficult to make evidence-based decisions to prevent or reduce consumption-stage food waste in a cost-effective manner
Parts verification for multi-level-dependent demand manufacturing systems: a recognition and classification structure
This research has developed and implemented a part recognition and classification structure to execute parts verification in a multi-level dependent demand manufacturing system. The part recognition algorithm enables the parent and child relationship between parts to be recognised in a finite-capacitated manufacturing system. This algorithm was developed using SIMAN simulation language and implemented in a multi-level dependent demand manufacturing simulation model. The part classification structure enables the modelling of a multi-level dependent demand manufacturing between parts to be carried out effectively. The part classification structure was programmed using Visual Basic Application (VBA) and was integrated to the work-to-list generated from a simulated MRP model. This part classification structure was then implemented in the multi-level dependent demand manufacturing simulation model. Two stages of implementation, namely parameterisation and execution, of the part recognition and classification structure were carried out. A real case study was used and five detail steps of execution were processed. Simulation experiments and MRP were run to verify and validate the part recognition and classification structure. The results led to the conclusion that implementation of the recognition and classification structure has effectively verified the correct parts and sub-assemblies used for the correct product and order. No parts and sub-assemblies shortages were found, and the quantity required was produced. The scheduled release for some orders was delayed due to overload of the required resources. When the loading is normal, all scheduled release timing is adhered to. The recognition and classification structure has a robust design; hence it can be easily adapted to new systems parameter to study a different or more complex case
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