United Technologies Corporation is an American multinational conglomerate headquartered in the United Technologies Building in Hartford, Connecticut. It researches, develops, and manufactures high-technology products in numerous areas, including aircraft engines, helicopters, HVAC, fuel cells, elevators and escalators, fire and security, building systems, and industrial products, among others. UTC is also a large military contractor, producing missile systems and military helicopters, most notably the UH-60 Black Hawk helicopter. Gregory Hayes is the current CEO. Wikipedia.
Magee A.,United Technologies
IEEE Communications Magazine | Year: 2010
As mobile backhaul networks migrate from legacy time-division-multiplex- based to packetswitched network infrastructures, the transport technology needs to address synchronization requirements once inherently provided by the network. This article explores key technology topics highlighting challenges to be considered in rolling out mobile backhaul synchronization solutions. © 2010 IEEE. Source
Li Z.,United Technologies
Energy and Buildings | Year: 2012
Vertical U-tube ground heat exchangers (GHEs) are a key component in geothermal energy utilization systems like ground source heat pumps (GSHPs). This paper presents a new constant heat flux model of its. Different from the existing uniform constant heat flux (UCHF) model, the model proposed in this paper is a cumulative constant heat flux (CCHF) model. The model is developed by reconstructing an experiment-verified three-dimensional unstructured finite-volume model. Applying the model, the borehole resistance with any geometric structure can be found. In addition, it may be used to develop the short time-step temperature response factors (TRFs) for simulating the behavior of the GHE on a short-time-step basis (one hour or less). © 2011 Elsevier B.V. Source
Agency: Cordis | Branch: H2020 | Program: IA | Phase: EeB-05-2015 | Award Amount: 4.75M | Year: 2015
OptEEmAL aims to develop an Optimised Energy Efficient Design Platform for refurbishment at district level, which will deliver an optimised, integrated and systemic design based on an Integrated Project Delivery (IPD) approach for building and district retrofitting projects, reducing time delivery and uncertainties, resulting in improved solutions when compared to business-as-usual practices. This main objective will be deployed through the following key objectives: 1. Development of a holistic and effective services platform for District Energy Efficient Retrofitting Design integrating interoperable modules and tools able to provide services for diagnosis, scenarios generation (according to stakeholders priorities), energy/ cost/ environment/ social evaluation, scenarios optimisation and data export. 2. Reinforcement of the presence of all involved stakeholders through an Integrated Project Delivery approach that will allow them being articulated through a collaborative and value-based process to deliver high-quality outcomes. 3. Development of an integrated ontology-based District Data Model that will contain key information in the fields of energy, comfort, environment (LCA), economic, social wellbeing and urban morphology. 4. Development of an Energy Conservation Measures catalogue (ECM) including technical, operational, maintenance and cost information giving valuable and consistent outputs to the design and district operation and maintenance stages. 5. Development of a bio-inspired optimization module based on Evolutionary computing with the aim to automate the decision making process to obtain the optimal design for an energy efficient retrofitting plan at district level. 6. Development of external connections of the OptEEmAL Platform to external entities (i.e. existing tools enabling the calculation of indicators to generate and optimise the retrofitting scenarios) 7. Strong disseminations, training, exploitation and market deployment strategies.
Agency: Cordis | Branch: FP7 | Program: CP-IP | Phase: SEC-2013.1.6-1 | Award Amount: 11.36M | Year: 2014
The LASIE project will design and develop a novel framework to assist forensic analysts in their investigations. The envisaged framework will be based on automated technology for advanced data processing supported by an important human component in critical decision making stages, as well as, legal and ethical aspects. The framework will consist of tools to automatically manipulate, analyse and fuse vast amounts of heterogeneous data acquired from different sources including CCTV surveillance content, confiscated desktops and hard disks, mobile devices, Internet, social networks, handwritten and calligraphic documents. The type of data considered includes text, images, video, audio and biometric information in multiple formats. In order to manage the results of the automated processing, a knowledge repository will be built. It will consider explicit analyst-knowledge and critical legacy information from previous cases. The proposed knowledge representation framework will also allow the system to provide recommendations to analysts, guide the investigation process and perform inference based on evidence extracted from available data. In LASIE, search and retrieval of evidence will be enhanced through the provision of complex query formulations and multimodal search mechanisms yet through a user-friendly, user-centric human-computer interface. The aim is to link and merge heterogeneous data retrieved from multiple sources to improve the knowledge-base and the accuracy of retrieved results. The envisaged user-friendly interface will allow analysts to easily visualise and navigate through the retrieved evidence, highlight relevant events and provide feedback to refine their search criteria. LASIE will follow a privacy-by-design approach, ensuring that all the aforementioned functionalities and the used forensic data strictly obey all legal and ethical restrictions and national laws. This ensures that the outcomes of the system will be accepted in European courts of law.
Agency: Cordis | Branch: H2020 | Program: RIA | Phase: EE-13-2015 | Award Amount: 2.00M | Year: 2016
Intelligent Energy Europe expects district heating to double its share of the European heat market by 2020 while district cooling will grow to 25%. While this expansion will translate into 2.6% reduction in the European primary energy need and 9.3% of all carbon emissions, it will not be achieved through modernization and expansion alone but requires fundamental technological innovation to make the next generation of district heating and cooling (DHC) systems highly efficient and cost effective to design, operate and maintain. E2District aims to develop, deploy, and demonstrate a novel cloud enabled management framework for DHC systems, which will deliver compound energy cost savings of 30% through development of a District Simulation Platform to optimise DHC asset configuration targeting >5% energy reduction, development of intelligent adaptive DHC control and optimisation methods targeting an energy cost reduction between 10 and 20%, including flexible production, storage and demand assets, and system-level fault detection and diagnostics, development of behaviour analytics and prosumer engagement tools to keep the end user in the loop, targeting overall energy savings of 5%. Development of a flexible District Operation System for the efficient, replicable and scalable deployment of DHC monitoring, intelligent control, FDD and prosumer engagement, development of novel business models for DHC Operators, Integrators and Designers, validation, evaluation, and demonstration of the E2District platform, and development of strong and rigorous dissemination, exploitation and path-to-market strategies to ensure project outcomes are communicated to all DHC stakeholders. E2District addresses specifically the calls objective related to the development of optimisation, control, metering, planning and modelling tools including consumer engagement and behaviour analytics and supports the integration of multiple generation sources, including renewable energy and storage.