Zero carbon manufacturing facility - Towards integrating material, energy, and waste process flows

The increasing pressure on material availability, energy prices, as well as emerging environmental legislation is leading manufacturers to adopt solutions to reduce their material and energy consumption as well as their carbon footprint, thereby becoming more sustainable. Ultimately manufacturers could potentially become zero carbon by having zero net energy demand and zero waste across the supply chain. The literature on zero carbon manufacturing and the technologies that underpin it are growing, but there is little available on how a manufacturer undertakes the transition. Additionally, the work in this area is fragmented and clustered around technologies rather than around processes that link the technologies together. There is a need to better understand material, energy, and waste process flows in a manufacturing facility from a holistic viewpoint. With knowledge of the potential flows, design methodologies can be developed to enable zero carbon manufacturing facility creation. This paper explores the challenges faced when attempting to design a zero carbon manufacturing facility. A broad scope is adopted from legislation to technology and from low waste to consuming waste. A generic material, energy, and waste flow model is developed and presented to show the material, energy, and waste inputs and outputs for the manufacturing system and the supporting facility and, importantly, how they can potentially interact. Finally the application of the flow model in industrial applications is demonstrated to select appropriate technologies and configure them in an integrated way. © 2009 IMechE.

Frictional flow of damp granular material in a conical centrifuge

An analysis is given of velocity and pressure-dependent sliding flow of a thin layer of damp granular material in a spinning cone. Integral momentum equations for steady state, axisymmetric flow are derived using a boundary layer approximation. These reduce to two coupled first-order differential equations for the radial and circumferential sliding velocities. The influence of viscosity and friction coefficients and inlet boundary conditions is explored by presentation of a range of numerical results. In the absence of any interfacial shear traction the flow would, with increasing radial and circumferential slip, follow a trajectory from inlet according to conservation of angular momentum and kinetic energy. Increasing viscosity or friction reduces circumferential slip and, in general, increases the residence time of a particle in the cone. The residence time is practically insensitive to the inlet velocity. However, if the cone angle is very close to the friction angle then the residence time is extremely sensitive to the relative magnitude of these angles. © 2011 Authors.

Optimization of thermal material in a flux pump system with high temperature superconductor

Superconductors are known for the ability to trap magnetic field. A thermally actuated magnetization (TAM) flux pump is a system that utilizes the thermal material to generate multiple small magnetic pulses resulting in a high magnetization accumulated in the superconductor. Ferrites are a good thermal material candidate for the future TAM flux pumps because the relative permeability of ferrite changes significantly with temperature, particularly around the Curie temperature. Several soft ferrites have been specially synthesized to reduce the cost and improve the efficiency of the TAM flux pump. Various ferrite compositions have been tested under a temperature variation ranging from 77K to 300K. The experimental results of the synthesized soft ferrites-Cu 0.3 Zn 0.7Ti 0.04Fe 1.96O 4, including the Curie temperature, magnetic relative permeability and the volume magnetization (emu/cm3), are presented in this paper. The results are compared with original thermal material, gadolinium, used in the TAM flux pump system.-Cu 0.3 Zn 0.7Ti 0.04 Fe 1.96O 4 holds superior characteristics and is believed to be a suitable material for next generation TAM flux pump. © 2011 IEEE.

Construction site image retrieval based on material cluster recognition

The capability to automatically identify shapes, objects and materials from the image content through direct and indirect methodologies has enabled the development of several civil engineering related applications that assist in the design, construction and maintenance of construction projects. This capability is a product of the technological breakthroughs in the area of image processing that has allowed for the development of a large number of digital imaging applications in all industries. In this paper, an automated and content based construction site image retrieval method is presented. This method is based on image retrieval techniques, and specifically those related with material and object identification and matches known material samples with material clusters within the image content. The results demonstrate the suitability of this method for construction site image retrieval purposes and reveal the capability of existing image processing technologies to accurately identify a wealth of materials from construction site images.

Material-Based Construction Site Image Retrieval

The technological advancements in digital imaging, the widespread popularity of digital cameras, and the increasing demand by owners and contractors for detailed and complete site photograph logs have triggered an ever-increasing growth in the rate of construction image data collection, with thousands of images being stored for each project. However, the sheer volume of images and the difficulties in accurately and manually indexing them have generated a pressing need for methods that can index and retrieve images with minimal or no user intervention. This paper reports recent developments from research efforts in the indexing and retrieval of construction site images in architecture, engineering, construction, and facilities management image database systems. The limitations and benefits of the existing methodologies will be presented, as well as an explanation of the reasons for the development of a novel image retrieval approach that not only can recognize construction materials within the image content in order to index images, but also can be compatible with existing retrieval methods, enabling enhanced results.