Assessment of Potential Carbon Dioxide-Based Demand Control Ventilation System Performance in Single Zone Systems

Heating, ventilation, and air conditioning (HVAC) use accounts for 43% of commercial energy consumption, with close to 5% used for ventilation purposes. Federal government agencies face both energy consumption reduction mandates and reduced funding. Carbon dioxide (CO2) based demand control ventilation (DCV) is a technology that allows for reduced energy consumption by allowing facility designers to introduce outside air based on facility occupancy, per American Society of Heating, Refrigeration, and Air Conditioning Engineers (ASHRAE) standards. This research aims to create a generalized methodology assessing energy and cost reductions from CO2-based DCV and then apply it to a specific facility at multiple locations. This research creates a generalized methodology for future researchers to follow based on the present body of knowledge. The model application then applies this methodology to one of the Department of Energy\u27s (DOE) commercial benchmark facility models. The selected DOE model is a small office building with single zone HVAC air systems, assessing DCV impact on energy consumption and costs for 52 United States locations. Although the model application is not life cycle cost effective for the building modeled, it successfully identifies which areas experience the greatest cost and energy savings from DCV

Semantic Models and Reasoning for Building System Operations: Focus on Knowledge-Based Control and Fault Detection for HVAC

According to the U.S. Energy Information Administration (EIA), the Building Sector consumes nearly half (47.6%) of all energy produced in the United States. Seventy-five percent (74.9%) of the electricity produced in the United States is used just to operate buildings. At the same time, decision making for building operations still heavily rely on human knowledge and practical experience and may be far from optimal. In a step toward mitigating these deficiencies, this dissertation reports on a program of research to identify opportunities for using semantic models and reason- ing in building system operations. The work focuses on knowledge-based control and fault detection for heating, ventilation and air conditioning (HVAC) systems. Decision-making procedures for building system operations are complicated by the multiplicity of participating domains (e.g., architecture, equipment, sensors, occu- pants, weather, utilities) that need to be considered. The key opportunity of this approach is a means to utilize semantic models for knowledge representation, inte- gration of heterogeneous data sources, and executable processing of semantic graph models in response to external events. The results of this dissertation are con- densed into three case-study applications; (1) Semantic-assisted model predictive control (MPC) for detection of occupant thermal comfort, (2) Semantic-based util- ity description for MPC in a chiller plant operation, and (3) Knowledge-based fault detection and diagnostics for HVAC systems

Contributions to IEEE 802.11-based long range communications

The most essential part of the Internet of Things (IoT) infrastructure is the wireless communication system that acts as a bridge for the delivery of data and control messages between the connected things and the Internet. Since the conception of the IoT, a large number of promising applications and technologies have been developed, which will change different aspects in our daily life. However, the existing wireless technologies lack the ability to support a huge amount of data exchange from many battery-driven devices, spread over a wide area. In order to support the IoT paradigm, IEEE 802.11ah is an Internet of Things enabling technology, where the efficient management of thousands of devices is a key function. This is one of the most promising and appealing standards, which aims to bridge the gap between traditional mobile networks and the demands of the IoT. To this aim, IEEE 802.11ah provides the Restricted Access Window (RAW) mechanism, which reduces contention by enabling transmissions for small groups of stations. Optimal grouping of RAW stations requires an evaluation of many possible configurations. In this thesis, we first discuss the main PHY and MAC layer amendments proposed for IEEE 802.11ah. Furthermore, we investigate the operability of IEEE 802.11ah as a backhaul link to connect devices over possibly long distances. Additionally, we compare the aforementioned standard with previous notable IEEE 802.11 amendments (i.e. IEEE 802.11n and IEEE 802.11ac) in terms of throughput (with and without frame aggregation) by utilizing the most robust modulation schemes. The results show an improved performance of IEEE 802.11ah (in terms of power received at long range while experiencing different packet error rates) as compared to previous IEEE 802.11 standards. Additionally, we expose the capabilities of future IEEE 802.11ah in supporting different IoT applications. In addition, we provide a brief overview of the technology contenders that are competing to cover the IoT communications framework. Numerical results are presented showing how the future IEEE 802.11ah specification offers the features required by IoT communications, thus putting forward IEEE 802.11ah as a technology to cater the needs of the Internet of Things paradigm. Finally, we propose an analytical model (named e-model) that provides an evaluation of the RAW onfiguration performance, allowing a fast adaptation of RAW grouping policies, in accordance to varying channel conditions. We base the e-model in known saturation models, which we adapted to include the IEEE 802.11ah’s PHY and MAC layer modifications and to support different bit rate and packet sizes. As a proof of concept, we use the proposed model to compare the performance of different grouping strategies,showing that the e-model is a useful analysis tool in RAW-enabled scenarios. We validate the model with existing IEEE 802.11ah implementation for ns-3.La clave del concepto Internet de las cosas (IoT) es que utiliza un sistema de comunicación inalámbrica, el cual actúa como puente para la entrega de datos y mensajes de control entre las "cosas" conectadas y el Internet. Desde la concepción del IoT, se han desarrollado gran cantidad de aplicaciones y tecnologías prometedoras que cambiarán distintos aspectos de nuestra vida diaria.Sin embargo, las tecnologías de redes computacionales inalámbricas existentes carecen de la capacidad de soportar las características del IoT, como las grandes cantidades de envío y recepción de datos desde múltiples dispositivos distribuidos en un área amplia, donde los dispositivos IoT funcionan con baterías. Para respaldar el paradigma del IoT, IEEE 802.11ah, la cual es una tecnología habilitadora del Internet de las cosas, para el cual la gestión eficiente de miles de dispositivos es una función clave. IEEE 802.11ah es uno de los estándares más prometedores y atractivos, desde su concepción orientada para IoT, su objetivo principal es cerrar la brecha entre las redes móviles tradicionales y la demandada por el IoT. Con este objetivo en mente, IEEE 802.11ah incluye entre sus características especificas el mecanismo de ventana de acceso restringido (RAW, por sus siglas en ingles), el cual define un nuevo período de acceso al canal libre de contención, reduciendo la misma al permitir transmisiones para pequeños grupos de estaciones. Nótese que para obtener una agrupación óptima de estaciones RAW, se requiere una evaluación de las distintas configuraciones posibles. En esta tesis, primero discutimos las principales mejoras de las capas PHY y MAC propuestas para IEEE 802.11ah. Además, investigamos la operatividad de IEEE 802.11ah como enlace de backhaul para conectar dispositivos a distancias largas. También, comparamos el estándar antes mencionado con las notables especificaciones IEEE 802.11 anteriores (es decir, IEEE 802.11n y IEEE 802.11ac), en términos de rendimiento (incluyendo y excluyendo la agregación de tramas de datos) y utilizando los esquemas de modulación más robustos. Los resultados muestran mejores resultados en cuanto al rendimiento de IEEE 802.11ah (en términos de potencia recibida a largo alcance, mientras se experimentan diferentes tasas de error de paquetes de datos) en comparación con los estándares IEEE 802.11 anteriores.Además, exponemos las capacidades de IEEE 802.11ah para admitir diferentes aplicaciones de IoT. A su vez, proporcionamos una descripción general de los competidores tecnológicos, los cuales contienden para cubrir el marco de comunicaciones IoT. También se presentan resultados numéricos que muestran cómo la especificación IEEE 802.11ah ofrece las características requeridas por las comunicaciones IoT, presentando así a IEEE 802.11ah como una tecnología que puede satisfacer las necesidades del paradigma de Internet de las cosas.Finalmente, proponemos un modelo analítico (denominado e-model) que proporciona una evaluación del rendimiento utilizando la característica RAW con múltiples configuraciones, el cual permite una rápida adaptación de las políticas de agrupación RAW, de acuerdo con las diferentes condiciones del canal de comunicación. Basamos el e-model en modelos de saturación conocidos, que adaptamos para incluir las modificaciones de la capa MAC y PHY de IEEE 802.11ah y para poder admitir diferentes velocidades de transmisión de datos y tamaños de paquetes. Como prueba de concepto, utilizamos el modelo propuesto para comparar el desempeño de diferentes estrategias de agrupación, mostrando que el e-model es una herramienta de análisis útil en escenarios habilitados para RAW. Cabe mencionar que también validamos el modelo con la implementación IEEE 802.11ah existente para ns-3

Computation and measurements of flows in rooms

This thesis contributes to the numerical modelling of flows in ventilated rooms. A range of advanced turbulence models (non-linear low Reynolds number Reynolds Averaged Navier-Stokes (RANS), Large Eddy Simulation (LES) and hybrid LES/RANS models) are used to model the flow in four ventilated rooms. These describe the flow in a more physically consistent manner than the commonly used linear RANS models. The performances of Explicit Algebraic Stress Model (EASM) and, cubic eddyviscosity RANS model are first analysed on four benchmark flow configurations. They show significant accuracy improvements when compared to their linear equivalents. Flows in ventilated rooms are complex. Their numerical modelling required an accurate definition of the various boundary conditions. This is often lacking in the literature and hence, as part of this work, measurements in a controlled ventilated office (optimised for Computational Fluid Dynamics (CFD) modelling) have been done. The measurements comprise airflow velocities, temperatures, concentration decay and, a careful description of the room's boundary conditions under six ventilation settings. This room data is thus seen as ideal for validating of CFD codes when applied to room ventilation problems. The numerical investigations show that the predictions with zero- or, one-equation (k - 1) RANS models (commonly used in room ventilation modelling) are less accurate than those using two-equation k-e models. The study shows that the accuracy improvements of the EASM and cubic models are of lesser magnitude when applied to room ventilation modelling than when applied to the benchmark flow configurations. The cubic model in particular, besides being more numerically unstable than the other RANS models, does not always improve flow predictions when compared with its linear equivalent. The EASM, about 20 to 30% more computationally demanding than its linear equivalent, improves solution accuracy for most flow considered in this work. LES predictions have highest level of agreement with measurements. LES is however too computationally expensive to be used for practical engineering applications. The novel hybrid RANS/LES model presented appears promising. It has similar accuracy to LES at lower computational costs

A design guide for energy-efficient research laboratories

This document--A Design Guide for Energy-Efficient Research Laboratories--provides a detailed and holistic framework to assist designers and energy managers in identifying and applying advanced energy-efficiency features in laboratory-type environments. The Guide fills an important void in the general literature and compliments existing in-depth technical manuals. Considerable information is available pertaining to overall laboratory design issues, but no single document focuses comprehensively on energy issues in these highly specialized environments. Furthermore, practitioners may utilize many antiquated rules of thumb, which often inadvertently cause energy inefficiency. The Guide helps its user to: introduce energy decision-making into the earliest phases of the design process, access the literature of pertinent issues, and become aware of debates and issues on related topics. The Guide does focus on individual technologies, as well as control systems, and important operational factors such as building commissioning. However, most importantly, the Guide is intended to foster a systems perspective (e.g. right sizing) and to present current leading-edge, energy-efficient design practices and principles