Using real occupancy in retrofit decision-making: Reducing the performance gap in low utilisation higher education buildings

Retrofit analysis relies on intuition and faith in the simulations used to justify strategy selection. However, intuition is built upon belief systems which become increasing unjustifiable as building operation deviates from design whether in utilisation, occupant behaviours or climate models. Higher education facilities are known for persistently low but well recorded occupant presence and density, and therefore are susceptible to counterintuitive behaviours related to utilisation. When operation has little correlation with design it is possible for performance issues to appear to be symptoms of design considerations rather than direct root of the issue. Using an EnergyPlus and SBEM virtual case study based on a floor of a university building and class registration data this paper describes how lighting retrofit simulation alludes to intuitive thermal property and HVAC efficiency concerns where heating management is the primary cause for concern. In doing so, it demonstrates a new approach to scheduling utilisation in higher education facilities and a method of meaningfully modelling BMS systems in EnergyPlus as replacement for the efficiency credits method. Results are discussed in terms of relevance to legislative compliance, cost-benefit analysis and how the scheduling methods contribute to intuitive analysis of low utilisation buildings

Optical code division multiple access codes comparison in free space optics and optical fiber transmission medium

Performance of three different Optical Code Division Multiple Access codes namely Prime Code (PC), Quadratic Congruence (QC), and Khazani-Syed (KS) code are compared in Free Space Optic (FSO) and optical fiber transmission. The simulation results show that efficiency of a code family is medium-dependent. While one code family performs the best in fiber medium, it is not necessary that it acts the same in FSO. For instance, KS with code weight of 6 provides BER 10-12 at 600 m distance, while other codes cannot even reach to the threshold 10-9 at this point. However this code shows vulnerability against fiber dispersion. At 5 km fiber, it provides BER of 10-7, even less then PC with 10-8. In that point KS code with weight 6 attains the best performance with BER of 10-11

Variable - weight optical code division multiple access system using different detection schemes

In this paper a Variable Weight OCDMA (VWOCDMA) system using KS code with Direct Decoding (DD), Complementary Subtraction (CS) and AND subtraction detections is proposed. System performance is analyzed using mathematical approximation and software simulation. In mathematical analysis, the effects of Phase-Induced Intensity Noise, shot noise and thermal noise are taken into account. Bit Error Rate of different users is plotted as a function of received optical power per chip with varying the bit rates and number of active users. It has been shown that for different bit rates and number of users, system using DD has better performance than the system applying CS and AND detection. Using DD scheme, the number of active users are 100 while this value is 27 and 25 in case of using CS and AND detection, respectively, when the received optical power per chip is –10 dBm

A 40 Gb/s duty-cycle/polarization division multiplexing system

Ever increasing demand for higher bandwidth and capacity requests more efficient multiplexing techniques. To increase supportable subscribers in networks, hybrid fiber optic systems have been proposed lately. In this research work a combination of polarization division multiplexing (PDM) and duty-cycle division multiplexing (DCDM) system is proposed for long haul communication. In the proposed system each PDM channel carries 2-channel DCDM where each user is operating at data rate of 10 Gb/s which forms 2 × 2 × 10 Gb/s optical system. Results show that the bit error rate of 10-9 for worst user is achieved at received power per chip of 21.12 dBm and optical signal to noise ratio of 22.08. Furthermore, system analysis demonstrates that the proposed system can tolerate the ±10 ps/nm dispersion without any need for compensation

Variable weight spectral amplitude coding for multiservice OCDMA networks

The emergence of heterogeneous applications such as internet data, video streaming, and online gaming, brings in a demand for a network environ- ments with capability of supporting diverse Quality of Services (QoS). Prioritizing the services is essential to ensure the delivery of information is at their best. This paper proposes a new code family to support optical domain service differentiation using spectral amplitude coding techniques within an optical code division multiple access (OCDMA) scenario. A particular user or service has a varying weight applied in order to obtain the desired signal quality. The proposed variable-weight code (VW-code) is constructed based on basic multi-service (MS) code. Mathematical model is developed to for performance evaluation of VW-MS code. In addition, the properties of pro- posed code is compared with other VW-OCDMA codes. It is shown that the proposed VW-MS provide an optimal code length with minimum cross- correlation compared to other VW-codes. Performance of VW-MS designed for triple-play services operating at bit rates of 0.622, 1.25 and 2.5 Gbps is demonstrated

On-Demand Monitoring of Construction Projects through a Game-Like Hybrid Application of BIM and Machine Learning

While unavoidable, inspections, progress monitoring, and comparing as-planned with as-built conditions in construction projects do not readily add tangible intrinsic value to the end-users. In large-scale construction projects, the process of monitoring the implementation of every single part of buildings and reflecting them on the BIM models can become highly labour intensive and error-prone, due to the vast amount of data produced in the form of schedules, reports and photo logs. In order to address the mentioned methodological and technical gap, this paper presents a framework and a proof of concept prototype for on-demand automated simulation of construction projects, integrating some cutting edge IT solutions, namely image processing, machine learning, BIM and Virtual Reality. This study utilised the Unity game engine to integrate data from the original BIM models and the as-built images, which were processed via various computer vision techniques. These methods include object recognition and semantic segmentation for identifying different structural elements through supervised training in order to superimpose the real world images on the as-planned model. The proposed framework leads to an automated update of the 3D virtual environment with states of the construction site. This framework empowers project managers and stockholders with an advanced decision-making tool, highlighting the inconsistencies in an effective manner. This paper contributes to body knowledge by providing a technical exemplar for the integration of ML and image processing approaches with immersive and interactive BIM interfaces, the algorithms and program codes of which can help replicability of these approaches by other scholars

Data Driven Model Improved by Multi-Objective Optimisation for Prediction of Building Energy Loads

Machine learning (ML) has been recognised as a powerful method for modelling building energy consumption. The capability of ML to provide a fast and accurate prediction of energy loads makes it an ideal tool for decision-making tasks related to sustainable design and retrofit planning. However, the accuracy of these ML models is dependent on the selection of the right hyper-parameters for a specific building dataset. This paper proposes a method for optimising ML models for forecasting both heating and cooling loads. The technique employs multi-objective optimisation with evolutionary algorithms to search the space of possible parameters. The proposed approach not only tunes single model to precisely predict building energy loads but also accelerates the process of model optimisation. The study utilises simulated building energy data generated in EnergyPlus to validate the proposed method, and compares the outcomes with the regular ML tuning procedure (i.e. grid search). The optimised model provides a reliable tool for building designers and engineers to explore a large space of the available building materials and technologies

Machine learning based impedance estimation in power system

A passive machine learning based technique to estimate the impedance of the power grid at the point of common coupling of a converter interfaced distributed generation source is proposed. The proposed method is based on supervised learning and provides a fast and accurate estimation of the grid impedance without adversely impacting the power quality of the system. This method does not need an injection of additional signals to the grid and provides an accurate estimation of the grid impedance. Multi-objective NSGA-II algorithm is used for optimisation and tuning the random forest model for accurate estimation of both R and X The resistive and inductive reactance of grid is estimated using Random Forest model due to its capability in the prediction of multiple output values simultaneously

Investigation of 2D-WH/TS OCDMA system performance under the influence of PMD

The impact of a differential group delay (DGD) and polarization mode dispersion (PMD) on multi-wavelength picosecond code carriers used by two-dimensional wavelength-hopping time-spreading coding schemes in optical code division multiple access (2D-WH/TS OCDMA systems is investigated. Based on experimental data collected over ten days on a 111 km long commercially used fiber link PMD and DGD parameters are determined and used to find the code carriers temporal broadening. This information is then used to calculate the 2D-WH/TS OCDMA system performance degradation as a function of varying number of simultaneous users for different DGD