Design of generic modular reconfigurable platforms (GMRPS) for a product-oriented micro manufacturing system

With the proposition of the concept of product-service systems, many manufacturers are focusing on selling services or functionality rather than products. Industrial production is shifting production models from mass production to mass customization and highly personalized needs. As a result, there is a tendency for manufacturing system suppliers to develop product-oriented systems to responsively cope with the dynamic fast moving competitive market. The key features of such a manufacturing system are the reconfigurability and adaptability, which can enable the system respond to the changeable needs of customers quickly and adaptively. Therefore, one of the challenges for the micro manufacturing system provider has been the design of a reconfigurable machine platform which will provide the functionalities and flexibility required by the product-oriented systems. In this paper, a new micro manufacturing platform, i.e. a generic modular reconfigurable platform (GMRP) is proposed in order to provide an effective means for fabrication of high quality micro products at low cost in a responsive manner. The GMRP-based system aims to be a product-oriented reconfigurable, highly responsive manufacturing system particularly for high value nano/micro manufacturing purposes. To reuse components and decrease material consumption, GMRP is characterized by hybrid micro manufacturing processes, modularity of key components, and reconfigurability of machine platforms and key components. Furthermore, a practical methodology for the design of reconfigurable machine platforms is discussed against the requirements from product-driven micro manufacturing and its extension for adaptive production

Triaxial projected shell model approach

The projected shell model analysis is carried out using the triaxial Nilsson+BCS basis. It is demonstrated that, for an accurate description of the moments of inertia in the transitional region, it is necessary to take the triaxiality into account and perform the three-dimensional angular-momentum projection from the triaxial Nilsson+BCS intrinsic wavefunction.Comment: 9 pages, 2 figure

Nexus of thermal resilience and energy efficiency in buildings: A case study of a nursing home

Extreme weather events become more frequent and severe due to climate change. Although energy efficiency technologies can influence thermal resilience of buildings, they are traditionally studied separately, and their interconnections are rarely quantified. This study developed a methodology of modeling and analysis to provide insights into the nexus of thermal resilience and energy efficiency of buildings. We conducted a case study of a real nursing home in Florida, where 12 patients died during Hurricane Irma in 2017 due to HVAC system power loss, to understand and quantify how passive and active energy efficiency measures (EEMs) can improve thermal resilience to reduce heat-exposure risk of patients. Results show that passive measures of opening windows and doors for natural ventilation, as well as miscellaneous load reduction, are very effective in eliminating the extreme dangerous occasions. However, to maintain safe conditions, active measures such as on-site power generators and thermal storage are also needed. The nursing home was further studied by changing its location to two other cities: San Francisco (mild climate) and Chicago (cold winter and hot summer). Results revealed that the EEMs' impacts on thermal resilience vary significantly by climate and building characteristics. The study also estimated the costs of EEMs to help stakeholders prioritize the measures. Passive measures that may not save energy may greatly improve thermal resilience, and thus should be considered in building design or retrofit. Findings from this study indicate energy efficiency technologies should be evaluated not only by their energy savings performance but also by their influence on a building's resilience to extreme weather events

Kinetics of dissociative chemisorption of methane and ethane on Pt(110)-(1X2)

The initial probability of dissociative chemisorption Pr of methane and ethane on the highly corrugated, reconstructed Pt(110)‐(1×2) surface has been measured in a microreactor by counting the number of carbon atoms on the surface following the reaction of methane and ethane on the surface which was held at various constant temperatures between 450 and 900 K during the reaction. Methane dissociatively chemisorbs on the Pt(110)‐(1×2) surface with an apparent activation energy of 14.4 kcal/mol and an apparent preexponential factor of 0.6. Ethane chemisorbs dissociatively with an apparent activation energy of 2.8 kcal/mol and an apparent preexponential factor of 4.7×10^(−3). Kinetic isotope effects were observed for both reactions. The fact that P_r is a strong function of surface temperature implies that the dissociation reactions proceed via a trapping‐mediated mechanism. A model based on a trapping‐mediated mechanism is used to explain the observed kinetic behavior. Kinetic parameters for C–H bond dissociation of the thermally accommodated methane and ethane are extracted from the model

Microscopic Description of Band Structure at Very Extended Shapes in the A ~ 110 Mass Region

Recent experiments have confirmed the existence of rotational bands in the A \~ 110 mass region with very extended shapes lying between super- and hyper-deformation. Using the projected shell model, we make a first attempt to describe quantitatively such a band structure in 108Cd. Excellent agreement is achieved in the dynamic moment of inertia J(2) calculation. This allows us to suggest the spin values for the energy levels, which are experimentally unknown. It is found that at this large deformation, the sharply down-sloping orbitals in the proton i_{13/2} subshell are responsible for the irregularity in the experimental J(2), and the wave functions of the observed states have a dominant component of two-quasiparticles from these orbitals. Measurement of transition quadrupole moments and g-factors will test these findings, and thus can provide a deeper understanding of the band structure at very extended shapes.Comment: 4 pages, 3 eps figures, final version accepted by Phys. Rev. C as a Rapid Communicatio

Space-Time Sampling for Network Observability

Designing sparse sampling strategies is one of the important components in having resilient estimation and control in networked systems as they make network design problems more cost-effective due to their reduced sampling requirements and less fragile to where and when samples are collected. It is shown that under what conditions taking coarse samples from a network will contain the same amount of information as a more finer set of samples. Our goal is to estimate initial condition of linear time-invariant networks using a set of noisy measurements. The observability condition is reformulated as the frame condition, where one can easily trace location and time stamps of each sample. We compare estimation quality of various sampling strategies using estimation measures, which depend on spectrum of the corresponding frame operators. Using properties of the minimal polynomial of the state matrix, deterministic and randomized methods are suggested to construct observability frames. Intrinsic tradeoffs assert that collecting samples from fewer subsystems dictates taking more samples (in average) per subsystem. Three scalable algorithms are developed to generate sparse space-time sampling strategies with explicit error bounds.Comment: Submitted to IEEE TAC (Revised Version