Part load operation coefficient of air-conditioning system of public building

IPLV overall coefficient, presented by Air-Conditioning and Refrigeration Institute (ARI) of America, shows running/operation status of air-conditioning system host only. For overall operation coefficient, logical solution has not been developed, to reflect the whole air-conditioning system under part load. In this research undertaking, the running time proportions of air-conditioning systems under part load have been obtained through analysis on energy consumption data during practical operation in all public buildings in Chongqing. This was achieved by using analysis methods, based on the statistical energy consumption data distribution of public buildings month-by-month. Comparing with the weight number of IPLV, part load operation coefficient of air-conditioning system, based on this research, does not only show the status of system refrigerating host, but also reflects and calculate energy efficiency of the whole air-conditioning system. The coefficient results from the processing and analyzing of practical running data, shows the practical running status of area and building type (actual and objective) – not clear. The method is different from model analysis which gets IPLV weight number, in the sense that this method of coefficient results in both four equal proportions and also part load operation coefficient of air-conditioning system under any load rate as necessary.

A generic model of Exergy Assessment of the Environmental Impact for the Building Lifecycle

A generic model of Exergy Assessment is proposed for the Environmental Impact of the Building Lifecycle, with a special focus on the natural environment. Three environmental impacts: energy consumption, resource consumption and pollutant discharge have been analyzed with reference to energy-embodied exergy, resource chemical exergy and abatement exergy, respectively. The generic model of Exergy Assessment of the Environmental Impact of the Building Lifecycle thus formulated contains two sub-models, one from the aspect of building energy utilization and the other from building materials use. Combined with theories by ecologists such as Odum, the paper evaluates a building's environmental sustainability through its exergy footprint and environmental impacts. A case study from Chongqing, China illustrates the application of this method. From the case study, it was found that energy consumption constitutes 70–80% of the total environmental impact during a 50-year building lifecycle, in which the operation phase accounts for 80% of the total environmental impact, the building material production phase 15% and 5% for the other phases.

A novel heteroditopic terpyridine-pincer ligand as building block for mono- and heterometallic Pd(II) and Ru(II) complexes

A palladium-catalyzed Stille coupling reaction was employed as a versatile method for the synthesis of a novel terpyridine-pincer (3, TPBr) bridging ligand, 4'-{4-BrC6H2(CH2NMe2)(2)-3,5}-2,2':6',2 ''-terpyridine. Mononuclear species [PdX(TP)] (X = Br, Cl), [Ru(TPBr)(tpy)](PF6)(2), and [Ru(TPBr)(2)](PF6)(2), synthesized by selective metalation of the NCNBr-pincer moiety or complexation of the terpyridine of the bifunctional ligand TPBr, were used as building blocks for the preparation of heterodi- and trimetallic complexes [Ru(TPPdCl)(tpy)](PF6)(2) (7) and [Ru(TPPdCl)(2)]-(PF6)(2) (8). The molecular structures in the solid state of [PdBr(TP)] (4a) and [Ru(TPBr)(2)](PF6)(2) (6) have been determined by single-crystal X-ray analysis. Electrochemical behavior and photophysical properties of the mono-and heterometallic complexes are described. All the above di- and trimetallic Ru complexes exhibit absorption bands attributable to (MLCT)-M-1 (Ru -> tpy) transitions. For the heteroleptic complexes, the transitions involving the unsubstituted tpy ligand are at a lower energy than the tpy moiety of the TPBr ligand. The absorption bands observed in the electronic spectra for TPBr and [PdCl(TP)] have been assigned with the aid of TD-DFT calculations. All complexes display weak emission both at room temperature and in a butyronitrile glass at 77 K. The considerable red shift of the emission maxima relative to the signal of the reference compound [Ru(tpy)(2)](2+) indicates stabilization of the luminescent (MLCT)-M-3 state. For the mono- and heterometallic complexes, electrochemical and spectroscopic studies (electronic absorption and emission spectra and luminescence lifetimes recorded at room temperature and 77 K in nitrile solvents), together with the information gained from IR spectroelectrochemical studies of the dimetallic complex [Ru(TPPdSCN)(tpy)](PF6)(2), are indicative of charge redistribution through the bridging ligand TPBr. The results are in line with a weak coupling between the {Ru(tpy)(2)} chromophoric unit and the (non)metalated NCN-pincer moiety.

Implementing intelligent cores using processor virtualization for fault tolerance

Processor virtualization for process migration in distributed parallel computing systems has formed a significant component of research on load balancing. In contrast, the potential of processor virtualization for fault tolerance has been addressed minimally. The work reported in this paper is motivated towards extending concepts of processor virtualization towards ‘intelligent cores’ as a means to achieve fault tolerance in distributed parallel computing systems. Intelligent cores are an abstraction of the hardware processing cores, with the incorporation of cognitive capabilities, on which parallel tasks can be executed and migrated. When a processing core executing a task is predicted to fail the task being executed is proactively transferred onto another core. A parallel reduction algorithm incorporating concepts of intelligent cores is implemented on a computer cluster using Adaptive MPI and Charm ++. Preliminary results confirm the feasibility of the approach.

An MPI-based implementation of intelligent agents on clusters

Recent research in multi-agent systems incorporate fault tolerance concepts, but does not explore the extension and implementation of such ideas for large scale parallel computing systems. The work reported in this paper investigates a swarm array computing approach, namely 'Intelligent Agents'. A task to be executed on a parallel computing system is decomposed to sub-tasks and mapped onto agents that traverse an abstracted hardware layer. The agents intercommunicate across processors to share information during the event of a predicted core/processor failure and for successfully completing the task. The feasibility of the approach is validated by implementation of a parallel reduction algorithm on a computer cluster using the Message Passing Interface.

Intelligent agents for fault tolerance: from multi-agent simulation to cluster-based implementation

Recent research in multi-agent systems incorporate fault tolerance concepts, but does not explore the extension and implementation of such ideas for large scale parallel computing systems. The work reported in this paper investigates a swarm array computing approach, namely 'Intelligent Agents'. A task to be executed on a parallel computing system is decomposed to sub-tasks and mapped onto agents that traverse an abstracted hardware layer. The agents intercommunicate across processors to share information during the event of a predicted core/processor failure and for successfully completing the task. The feasibility of the approach is validated by simulations on an FPGA using a multi-agent simulator, and implementation of a parallel reduction algorithm on a computer cluster using the Message Passing Interface.

A cluster-based implementation of a fault-tolerant parallel reduction algorithm using swarm-array computing

Recent research in multi-agent systems incorporate fault tolerance concepts. However, the research does not explore the extension and implementation of such ideas for large scale parallel computing systems. The work reported in this paper investigates a swarm array computing approach, namely ‘Intelligent Agents’. In the approach considered a task to be executed on a parallel computing system is decomposed to sub-tasks and mapped onto agents that traverse an abstracted hardware layer. The agents intercommunicate across processors to share information during the event of a predicted core/processor failure and for successfully completing the task. The agents hence contribute towards fault tolerance and towards building reliable systems. The feasibility of the approach is validated by simulations on an FPGA using a multi-agent simulator and implementation of a parallel reduction algorithm on a computer cluster using the Message Passing Interface.