High-Performance Integrated Window and Façade Solutions for California

The researchers developed a new generation of high-performance façade systems and supporting design and management tools to support industry in meeting California’s greenhouse gas reduction targets, reduce energy consumption, and enable an adaptable response to minimize real-time demands on the electricity grid. The project resulted in five outcomes: (1) The research team developed an R-5, 1-inch thick, triplepane, insulating glass unit with a novel low-conductance aluminum frame. This technology can help significantly reduce residential cooling and heating loads, particularly during the evening. (2) The team developed a prototype of a windowintegrated local ventilation and energy recovery device that provides clean, dry fresh air through the façade with minimal energy requirements. (3) A daylight-redirecting louver system was prototyped to redirect sunlight 15–40 feet from the window. Simulations estimated that lighting energy use could be reduced by 35–54 percent without glare. (4) A control system incorporating physics-based equations and a mathematical solver was prototyped and field tested to demonstrate feasibility. Simulations estimated that total electricity costs could be reduced by 9-28 percent on sunny summer days through adaptive control of operable shading and daylighting components and the thermostat compared to state-of-the-art automatic façade controls in commercial building perimeter zones. (5) Supporting models and tools needed by industry for technology R&D and market transformation activities were validated. Attaining California’s clean energy goals require making a fundamental shift from today’s ad-hoc assemblages of static components to turnkey, intelligent, responsive, integrated building façade systems. These systems offered significant reductions in energy use, peak demand, and operating cost in California

TEMPOS: A Platform for Developing Temporal Applications on Top of Object DBMS

This paper presents TEMPOS: a set of models and languages supporting the manipulation of temporal data on top of object DBMS. The proposed models exploit object-oriented technology to meet some important, yet traditionally neglected design criteria related to legacy code migration and representation independence. Two complementary ways for accessing temporal data are offered: a query language and a visual browser. The query language, namely TempOQL, is an extension of OQL supporting the manipulation of histories regardless of their representations, through fully composable functional operators. The visual browser offers operators that facilitate several time-related interactive navigation tasks, such as studying a snapshot of a collection of objects at a given instant, or detecting and examining changes within temporal attributes and relationships. TEMPOS models and languages have been formalized both at the syntactical and the semantical level and have been implemented on top of an object DBMS. The suitability of the proposals with regard to applications' requirements has been validated through concrete case studies

CAS-CNN: A Deep Convolutional Neural Network for Image Compression Artifact Suppression

Lossy image compression algorithms are pervasively used to reduce the size of images transmitted over the web and recorded on data storage media. However, we pay for their high compression rate with visual artifacts degrading the user experience. Deep convolutional neural networks have become a widespread tool to address high-level computer vision tasks very successfully. Recently, they have found their way into the areas of low-level computer vision and image processing to solve regression problems mostly with relatively shallow networks. We present a novel 12-layer deep convolutional network for image compression artifact suppression with hierarchical skip connections and a multi-scale loss function. We achieve a boost of up to 1.79 dB in PSNR over ordinary JPEG and an improvement of up to 0.36 dB over the best previous ConvNet result. We show that a network trained for a specific quality factor (QF) is resilient to the QF used to compress the input image - a single network trained for QF 60 provides a PSNR gain of more than 1.5 dB over the wide QF range from 40 to 76.Comment: 8 page

Merging enriched Finite Element triangle meshes for fast prototyping of alternate solutions in the context of industrial maintenance

A new approach to the merging of Finite Element (FE) triangle meshes is proposed. Not only it takes into account the geometric aspects, but it also considers the way the semantic information possibly associated to the groups of entities (nodes, faces) can be maintained. Such high level modification capabilities are of major importance in all the engineering activities requiring fast modifications of meshes without going back to the CAD model. This is especially true in the context of industrial maintenance where the engineers often have to solve critical problems in very short time. Indeed, in this case, the product is already designed, the CAD models are not necessarily available and the FE models might be tuned. Thus, the product behaviour has to be studied and improved during its exploitation while prototyping directly several alternate solutions. Such a framework also finds interest in the preliminary design phases where alternative solutions have to be simulated. The algorithm first removes the intersecting faces in an n-ring neighbourhood so that the filling of the created holes produces triangles whose sizes smoothly evolve according to the possibly heterogeneous sizes of the surrounding triagles. The holefilling algorithm is driven by an aspect ratio factor which ensures that the produced triangulation fits well the FE requirements. It is also constrained by the boundaries of the groups of entities gathering together the simulation semantic. The filled areas are then deformed to blend smoothly with the surroundings meshes

User perspective on AM-enabled mass customisation toolkits

Mass Customisation (MC) toolkits are powerful user interfaces that enable customers to engage in the design of their own products. This research follows design research methodology (integrated with design process) to research the user perspective on AM-enabled MC toolkits. This research proposes and validates a design framework to guide designers and software developers in designing a user-centred AM-enabled MC toolkits, enabled using digital fabrication technologies such as Additive Manufacturing (AM). This framework includes pre-implementation assessment, and implementation stages. An initial literature review revealed a lack of standard or universal norms for these user interfaces, and a lack of consistency in their design, in which web objects such as logo, product image, prices, etc. are not shared commonly among toolkits, nor occupy a frequent position. Furthermore, an optimum number of degree of freedom for MC toolkits is lacking from current design knowledge. This research focuses on AM-enabled Mass Customisation toolkits as a means to enable customers design; its concentration is on users. A first quantitative study was conducted to compare and rank of a collection of features. More detailed user requirements regarding the content and layout of MC toolkits were revealed in a workshop. As a part of the second study, four different CAD systems (software programs and 3D-enabling libraries) were used to create MC toolkits. This provided an understanding of the pros and cons of each system, and demonstrated Three.js to be the best system amongst each one s feasibility and application. Based on previous findings, and as a part of the UX-design process, a prototype web-based MC toolkit was constructed, utilising the Three.js library. The prototype was used for a second study as a platform to investigate, the user interaction and usability of the toolkit, to validate the toolkit design as well as provide insights for its improvement. Findings and reflections from all the studies were then visualised and communicated in an interactive design framework. A final study, conducted with professional users (N=4) assessed the usability and technicality of the framework tool and led to a number of suggested improvements. The main contributions to knowledge are: 1- a table was produced to compare the features of four different system, by which Three.js was identified as the most suitable among them 2- most important and expected features for the content were obtained from the user rankings, most frequent location of features for the layout was identified based on the users, and user insights were reflected based on the evaluation of the prototype 3- the UI needs to be flexible in term of degrees of freedom, in another words, each customer (novice or professional) is able to adjust the number of options presented. 4- a framework was proposed through reviewing and adapting existing guidelines and findings from this research