The use of fault detection and diagnostics to reduce air handling unit energy consumption

The contribution of buildings towards total worldwide energy consumption in developed countries is between 20% and 40%. Heating Ventilation and Air Conditioning (HVAC), and more specifically Air Handling Units (AHUs) energy consumption accounts on average for 40% of a typical medical device manufacturing or pharmaceutical facility’s energy consumption. Studies have indicated that 20 – 30% energy savings are achievable by recommissioning HVAC systems, and more specifically AHU operations, to rectify faulty operation. Automated Fault Detection and Diagnosis (AFDD) is a process concerned with potentially partially or fully automating the commissioning process through the detection of faults. An expert system is a knowledge-based system, which employs Artificial Intelligence (AI) methods to replicate the knowledge of a human subject matter expert, in a particular field, such as engineering, medicine, finance and marketing, to name a few. This thesis details the research and development work undertaken in the development and testing of a new AFDD expert system for AHUs which can be installed in minimal set up time on a large cross section of AHU types in a building management system vendor neutral manner. Both simulated and extensive field testing was undertaken against a widely available and industry known expert set of rules known as the Air Handling Unit Performance Assessment Rules (APAR) (and a later more developed version known as APAR_extended) in order to prove its effectiveness. Specifically, in tests against a dataset of 52 simulated faults, this new AFDD expert system identified all 52 derived issues whereas the APAR ruleset identified just 10. In tests using actual field data from 5 operating AHUs in 4 manufacturing facilities, the newly developed AFDD expert system for AHUs was shown to identify four individual fault case categories that the APAR method did not, as well as showing improvements made in the area of fault diagnosis.

Organometallic derivatives of cyclotriphosphazene as precursors of nanostructured metallic materials: a new solid state method

The cyclic phosphazene trimers [N3P3(OC6H5)5OC5H4N·Ti(Cp)2Cl][PF6] (3), [N3P3(OC6H4CH2CN·Ti(Cp)2Cl)6][PF6]6 (4), [N3P3(OC6H4-But)5(OC6H4CH2CN·Ti(Cp)2Cl)][PF6] (5), [N3P3(OC6H5)5C6H4CH2CN·Ru(Cp)(PPh3)2][PF6] (6), [N3P3(OC6H5)5C6H4CH2CN·Fe(Cp)(dppe)][PF6] (7) and N3P3(OC6H5)5OC5H4N·W(CO)5 (8) were prepared and characterized. As a model, the simple compounds [HOC5H5N·Ti(Cp)2Cl]PF6 (1) and [HOC6H4CH2CN·Ti(Cp)2Cl]PF6 (2) were also prepared and characterized. Pyrolysis of the organometallic cyclic trimers in air yields metallic nanostructured materials, which according to transmission and scanning electron microscopy (TEM/SEM), energy-dispersive X-ray microanalysis (EDX), and IR data, can be formulated as either a metal oxide, metal pyrophosphate or a mixture in some cases, depending on the nature and quantity of the metal, characteristics of the organic spacer and the auxiliary substituent attached to the phosphorus cycle. Atomic force microscopy (AFM) data indicate the formation of small island and striate nanostructures. A plausible formation mechanism which involves the formation of a cyclomatrix is proposed, and the pyrolysis of the organometallic cyclic phosphazene polymer as a new and general method for obtaining metallic nanostructured materials is discussed.