Sean Danaher

Building thermal model reduction using nonlinear constrained optimization

The short-time-horizon modelling of building thermal response is of relevance in situations where HVAC plant and control system analyses are of interest. In this precise area of building thermal modelling issues of model accuracy and computational efficiency become important. In this work a nonlinear constrained optimization method is used for reducing the model order of building elements. The approach involves minimizing the error between the step response of a high-order reference model whilst tuning the parameters of a lower order model in order to obtain an optimized reduced-order model. Results show that a reduced model based on a 2nd-order building element gives minimal loss of accuracy but significant improvements in computational effort when treating both high and low thermal capacity modelling problems.

Thermal comfort based fuzzy logic controller

Most heating, ventilation and air conditioning (HVAC) control systems are considered as temperature control problems. In this work, the predicted mean vote (PMV) is used to control the indoor temperature of a space by setting it at a point where the PMV index becomes zero and the predicted percentage of persons dissatisfied (PPD) achieves a maximum threshold of 5%. This is achieved through the use of a fuzzy logic controller that takes into account a range of human comfort criteria in the formulation of the control action that should be applied to the heating system to bring the space to comfort conditions. The resulting controller is free of the set up and tuning problems that hinder conventional HVAC controllers. Simulation results show that the proposed control strategy makes it possible to maximize the indoor thermal comfort and, correspondingly, a reduction in energy use of 20% was obtained for a typical 7-day winter period when compared with conventional control.

Low-order model for the simulation of a building and its heating system

Signifirant progress has been made in recent years on the development of modular and generic simulation programs for investigating the thermal behaviour of buildings and associated HVAC plant and controls. However, many of these programs are inflexible for the specific analysis of HVAC plant and control systems over short time scales. The nature of this inflexibility is discussed and a remedy is sought through the development of a low-order lumped-capacity thermal model of a building space. This is expressed as a linear time-invariant state-space description. A non-linear dynamic model of a hot water heating system with feedback control has been added and results under open-loop conditions are presented. The model has the advantage of simplicity and computational efficiency. Results are compared with field-monitored data obtained from a building in use and an excellent agreement between the two is demonstrated, though this comparison is restricted to a north-facing building space with high thermal capacity.

Application of an artificial neural network for modelling the thermal dynamics of a building's space and its heating system

Artificial neural networks (ANNs) have been used for modelling the thermal dynamics of a building’s space, its water heating system and the influence of solar radiation. A multi-layer feed-forward neural network, using a Levenberg-Marquardt backpropagation-training algorithm, has been applied to predict the future internal temperature. Real weather data for a number of winter months, together with a validated building model (based on the building constructions data), were used to train the network in order to generate a mapping between the easily measurable inputs (outdoor temperature, solar irradiance, heating valve position and the building indoor temperature) and the desired output, i.e., the predicted indoor temperature. The objective of this work was to investigate the potential of using an ANN with singular value decomposition method (SVD) to predict the indoor temperature to shut down the heating system controller early for saving the energy consumption for heating inside the building.

Study of the acoustic signature of UHE neutrino interactions in water and ice

The production of acoustic signals from the interactions of ultra-high energy (UHE) cosmic ray neutrinos in water and ice has been studied. A new computationally fast and efficient method of deriving the signal is presented. This method allows the implementation of up to date parameterisations of acoustic attenuation in seawater and ice that now includes the effects of complex attenuation, where appropriate. The methods presented here have been used to compute and study the properties of the acoustic signals which would be expected from such interactions. A matrix method of parameterising the signals, which includes the expected fluctuations, is also presented. These methods are used to generate the expected signals that would be detected in acoustic UHE neutrino telescopes.

First data from ACoRNE and signal processing techniques

This paper attempts to estimate the performance of the Rona naval acoustic hydrophone array which has been recently upgraded to act as a test bed for an EeV neutrino detector. Preliminary estimation of the array performance is presented together with some preliminary data analysis and reduction techniques.

Simple techniques for generating nanosecond blue light pulses from light emitting diodes

The electronic drive requirements for producing nanosecond optical pulses from blue light emitting diodes are considered. Simple circuits are used to generate the fast current pulses necessary to switch on and assist with the turn off of these devices. The intensity of the emitted radiation can be controlled by the magnitude of the drive current. Optical pulses in the nanosecond range are suitable for, but not limited to, the calibration of scintillation counters. The circuits described can be either free running or externally triggered. Typically, the optical pulse full width half maximum (FWHM) is below 1 ns. The presented techniques are not limited to blue LEDs and should be applicable to devices of longer wavelengths.

Development of an Ultrasonic Airflow Measurement Device for Ducted Air

In this study, an in-duct ultrasonic airflow measurement device has been designed, developed and tested. The airflow measurement results for a small range of airflow velocities and temperatures show that the accuracy was better than 3.5% root mean square (RMS) when it was tested within a round or square duct compared to the in-line Venturi tube airflow meter used for reference. This proof of concept device has provided evidence that with further development it could be a low-cost alternative to pressure differential devices such as the orifice plate airflow meter for monitoring energy efficiency performance and reliability of ventilation systems. The design uses a number of techniques and design choices to provide solutions to lower the implementation cost of the device compared to traditional airflow meters. The design choices that were found to work well are the single sided transducer arrangement for a “V” shaped reflective path and the use of square wave transmitter pulses ending with the necessary 180° phase changed pulse train to suppress transducer ringing. The device is also designed so that it does not have to rely on high-speed analogue to digital converters (ADC) and intensive digital signal processing, so could be implemented using voltage comparators and low-cost microcontrollers.

Investigation of the Equivalent Circuit Parameters and Design of a Dual Polarised Dual Frequency Aperture Coupled Microstrip Antenna

This communication presents a simplified approach to the design of a single feed dual polarised, dual frequency (1.9 and 2.4 GHz) aperture coupled microstrip antenna. Using simulation and practical investigation, the coupling between the microstrip feed line and aperture, along with the coupling between the aperture and patch, is investigated and modelled using equivalent transformers. The results obtained are used to reduce the number of interdependent design parameters, thereby allowing initial approximate values to be determined more directly with only fine tuning subsequently required to obtain good matching at both frequencies. Excellent agreement is obtained for the simulation and practical results of the return loss and the gain of the antenna.

Address-vector quantisation applied to speech coding

The use of address vector quantisation (VQ) in the compression of linear predictive coded (LPC) and line spectral pairs (LSP) speech parameters in a speaker dependent system are examined. Four speakers are investigated; two male and two female. The speech waveform is coded to LPC and LSP parameters using LPC techniques and is vector quantised using an unsupervised neural network, a Kohonen self organising feature map (KSOFM), to create a codebook of 128 entries. Address VQ is applied to the codebook and the data examined for recurring sequences to exploit redundancy. Preliminary results indicate that approximately 46% additional compression is achievable using this method. As Address VQ is a loss-less compression scheme, this reduction is achieved without any further reduction in speech quality.