Intelligent Approaches For Modeling And Optimizing Hvac Systems

Advanced energy management control systems (EMCS), or building automation systems (BAS), offer an excellent means of reducing energy consumption in heating, ventilating, and air conditioning (HVAC) systems while maintaining and improving indoor environmental conditions. This can be achieved through the use of computational intelligence and optimization. This research will evaluate model-based optimization processes (OP) for HVAC systems utilizing MATLAB, genetic algorithms and self-learning or self-tuning models (STM), which minimizes the error between measured and predicted performance data. The OP can be integrated into the EMCS to perform several intelligent functions achieving optimal system performance. The development of several self-learning HVAC models and optimizing the process (minimizing energy use) will be tested using data collected from the HVAC system servicing the Academic building on the campus of NC A&T State University. Intelligent approaches for modeling and optimizing HVAC systems are developed and validated in this research. The optimization process (OP) including the STMs with genetic algorithms (GA) enables the ideal operation of the building’s HVAC systems when running in parallel with a building automation system (BAS). Using this proposed optimization process (OP), the optimal variable set points (OVSP), such as supply air temperature (Ts), supply duct static pressure (Ps), chilled water supply temperature (Tw), minimum outdoor ventilation, reheat (or zone supply air temperature, Tz), and chilled water differential pressure set-point (Dpw) are optimized with respect to energy use of the HVAC’s cooling side including the chiller, pump, and fan. HVAC system component models were developed and validated against both simulated and monitored real data of an existing VAV system. The optimized set point variables minimize energy use and maintain thermal comfort incorporating ASHRAE’s new ventilation standard 62.1-2013. The proposed optimization process is validated on an existing VAV system for three summer months (May, June, August). This proposed research deals primarily with: on-line, self-tuning, optimization process (OLSTOP); HVAC design principles; and control strategies within a building automation system (BAS) controller. The HVAC controller will achieve the lowest energy consumption of the cooling side while maintaining occupant comfort by performing and prioritizing the appropriate actions. Recent technological advances in computing power, sensors, and databases will influence the cost savings and scalability of the system. Improved energy efficiencies of existing Variable Air Volume (VAV) HVAC systems can be achieved by optimizing the control sequence leading to advanced BAS programming. The program’s algorithms analyze multiple variables (humidity, pressure, temperature, CO2, etc.) simultaneously at key locations throughout the HVAC system (pumps, cooling coil, chiller, fan, etc.) to reach the function’s objective, which is the lowest energy consumption while maintaining occupancy comfort

Applications of satellite technology to broadband ISDN networks

Two satellite architectures for delivering broadband integrated services digital network (B-ISDN) service are evaluated. The first is assumed integral to an existing terrestrial network, and provides complementary services such as interconnects to remote nodes as well as high-rate multicast and broadcast service. The interconnects are at a 155 Mbs rate and are shown as being met with a nonregenerative multibeam satellite having 10-1.5 degree spots. The second satellite architecture focuses on providing private B-ISDN networks as well as acting as a gateway to the public network. This is conceived as being provided by a regenerative multibeam satellite with on-board ATM (asynchronous transfer mode) processing payload. With up to 800 Mbs offered, higher satellite EIRP is required. This is accomplished with 12-0.4 degree hopping beams, covering a total of 110 dwell positions. It is estimated the space segment capital cost for architecture one would be about $190M whereas the second architecture would be about$250M. The net user cost is given for a variety of scenarios, but the cost for 155 Mbs services is shown to be about $15-22/minute for 25 percent system utilization

Dynamic Modeling, Sensor Placement Design, and Fault Diagnosis of Nuclear Desalination Systems

Fault diagnosis of sensors, devices, and equipment is an important topic in the nuclear industry for effective and continuous operation of nuclear power plants. All the fault diagnostic approaches depend critically on the sensors that measure important process variables. Whenever a process encounters a fault, the effect of the fault is propagated to some or all the process variables. The ability of the sensor network to detect and isolate failure modes and anomalous conditions is crucial for the effectiveness of a fault detection and isolation (FDI) system. However, the emphasis of most fault diagnostic approaches found in the literature is primarily on the procedures for performing FDI using a given set of sensors. Little attention has been given to actual sensor allocation for achieving the efficient FDI performance. This dissertation presents a graph-based approach that serves as a solution for the optimization of sensor placement to ensure the observability of faults, as well as the fault resolution to a maximum possible extent. This would potentially facilitate an automated sensor allocation procedure. Principal component analysis (PCA), a multivariate data-driven technique, is used to capture the relationships in the data, and to fit a hyper-plane to the data. The fault directions for different fault scenarios are obtained from the prediction errors, and fault isolation is then accomplished using new projections on these fault directions. The effectiveness of the use of an optimal sensor set versus a reduced set for fault detection and isolation is demonstrated using this technique. Among a variety of desalination technologies, the multi-stage flash (MSF) processes contribute substantially to the desalinating capacity in the world. In this dissertation, both steady-state and dynamic simulation models of a MSF desalination plant are developed. The dynamic MSF model is coupled with a previously developed International Reactor Innovative and Secure (IRIS) model in the SIMULINK environment. The developed sensor placement design and fault diagnostic methods are illustrated with application to the coupled nuclear desalination system. The results demonstrate the effectiveness of the newly developed integrated approach to performance monitoring and fault diagnosis with optimized sensor placement for large industrial systems

Measuring the effects of drugs on single cancer cell growth

Thesis (Ph. D.)--Massachusetts Institute of Technology, Computational and Systems Biology Program, 2012.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student submitted PDF version of thesis.Includes bibliographical references.Understanding the effectiveness of a drug therapy on halting disease progression is an essential aspect of cancer biology. Conventional assays that study cell behavior after a drug intervention report the average response of a cell population which can mask the heterogeneity and dynamics of seemingly identical cells. Recently, many single-cell techniques have been developed, but there are currently no methods that can fully characterize the long-term effects of drug treatment on cancer cell growth. To accomplish such, we developed an instrument to measure single-cell growth before and after drug treatment. In order to achieve femtogram-level mass resolution, we employed the suspended microchannel resonator (SMR), a vacuum-packaged cantilever with an embedded channel. Here, we describe three implementations that involve different technologies (optical trap, mechanical trap, and dynamic ow trapping) to capture a cell for repeated measurements and to perform drug delivery. Applying the technique we developed based on the dynamic ow trapping, we were able to monitor one or more generations of a cancer cell before and after drug treatment. We investigated the growth of mouse leukemia cells in response to drugs that inhibit the mammalian target of rapamycin (mTOR) pathway, induce apoptosis, or prevent translational activity directly at the ribosome. Our method was able to discern a particular growth signature for each drug investigated and to discover a new phenotype in cells following mTOR inhibition. Furthermore, our data demonstrates that the instantaneous growth rate changes following a drug treatment could potentially predict the long-term inhibitory effect on cellular biogenesis and mass accumulation.by Yaochung Weng.Ph.D

Equation-oriented modeling, simulation, and optimization of integrated and intensified process and energy systems

Process intensification, defined as unconventional design and/or operation of processes that results in substantial performance improvements, represents a promising route toward reducing capital and operating expenses in the chemical/petrochemical process industry, while simultaneously achieving improved safety and environmental performance. In this dissertation, intensification is approached from three different angles: reactor design and control, process flowsheet design and optimization, and production scheduling and control. In the first part of the dissertation, three novel concepts for improving the controllability of intensified microchannel reactors are introduced. The first concept is a latent energy storage-based temperature controller, where a phase change material is confined within the walls of an autothermal reactor to improve local temperature control. The second concept is a segmented catalyst layer which modulates the rate of heat generation and consumption along the length of an autothermal reactor. Finally, the third concept is a thermally actuated valve, which uses small-scale bimetallic strips to modulate flow in a microchannel reactor in response to temperature changes. The second part of the dissertation introduces a novel framework for equation-oriented flowsheet modeling, simulation and optimization. The framework consists of a pseudo-transient reformulation of the steady-state material and energy balance equations of process unit operations as differential-algebraic equation (DAE) systems that are statically equivalent to the original model. I show that these pseudo-transient models improve the convergence properties of equation-oriented process flowsheet simulations by expanding the convergence basin in comparison to conventional steady state equation-oriented simulators. A library of pseudo-transient unit operation models is developed, and several case studies are presented. Models for more complex unit operations such as a pseudo-transient multistream heat exchanger and a dividing-wall distillation column are later introduced, and can easily be included in the flowsheet optimization framework. In the final part of the dissertation, a paradigm for calculating the optimal production schedule in a fast changing market situation is introduced. This is accomplished by including a model of the dynamics of a process and its control system into production scheduling calculations. The scheduling-relevant dynamic models are constructed to be of lower order than a detailed dynamic process model, while capturing the closed-loop behavior of a set of scheduling-relevant variables. Additionally, a method is given for carrying out these production scheduling calculations online and in "closed scheduling loop,"' i.e., recalculating scheduling decisions upon the advent of scheduling-relevant process or market events. An air separation unit operating in a demand response scenario is used as a representative case study.Chemical Engineerin

Gas Turbines

This book is intended to provide valuable information for the analysis and design of various gas turbine engines for different applications. The target audience for this book is design, maintenance, materials, aerospace and mechanical engineers. The design and maintenance engineers in the gas turbine and aircraft industry will benefit immensely from the integration and system discussions in the book. The chapters are of high relevance and interest to manufacturers, researchers and academicians as well

Modeling and Simulation in Engineering

This book provides an open platform to establish and share knowledge developed by scholars, scientists, and engineers from all over the world, about various applications of the modeling and simulation in the design process of products, in various engineering fields. The book consists of 12 chapters arranged in two sections (3D Modeling and Virtual Prototyping), reflecting the multidimensionality of applications related to modeling and simulation. Some of the most recent modeling and simulation techniques, as well as some of the most accurate and sophisticated software in treating complex systems, are applied. All the original contributions in this book are jointed by the basic principle of a successful modeling and simulation process: as complex as necessary, and as simple as possible. The idea is to manipulate the simplifying assumptions in a way that reduces the complexity of the model (in order to make a real-time simulation), but without altering the precision of the results

Supporting differentiated classes of resilience in multilayer networks

Services provided over telecommunications networks typically have different resilience requirements and networks need to be able to support different levels of resilience in an efficient manner. This dissertation investigates the problem of supporting differentiated classes of resilience in multilayer networks, including the most stringent resilience class required by critical services. We incorporate an innovative technique of embedding a subnetwork, termed the spine, with comparatively higher availability values at the physical layer. The spine lays a foundation for differentiation between multiple classes of flows that can be leveraged to achieve both high resilience and differentiation. The aim of this research is mainly to explore, design, and evaluate the proposed spine concept model in multilayer networks. The dissertation has four major parts. First, we explore the spine concept through numerical analysis of simple topologies illustrating the potential benefits and the cost considerations of the spine. We develop heuristics algorithms to find suitable spines for a network based on the structural properties of the network topology. Second, an optimization problem is formulated to determine the spine. The problem encompasses estimates of link availability improvements, associated costs, and a total budget. Third, we propose a crosslayer mapping and spine-aware routing design problem with protection given mainly at the lower layer. The problem is designed to transfer lower layer differentiation capability to the upper layer network and flows. We provide two joint routing-mapping optimization formulations and evaluate their performance in a multilayer scenario. Fourth, the joint routing-mapping problem is redesigned with protection given in the upper network layer instead. This will create two isolated logical networks; one mapped to the spine and the other is mapped freely on the network. Flows are assigned a path or path-pair based on their class of resilience. This approach can provide more routing options yielding different availability levels. The joint routing-mapping design problems are formulated as Integer Linear Programming (ILP) models. The goal is to achieve a wider range of availability values across layers and high availability levels for mission-critical services without the need to use higher order protection configurations. The proposed models are evaluated with extensive numerical results using real network topologies

Renewable Energy

This book discusses renewable energy resources and systems as well as energy efficiency. It contains twenty-three chapters over six sections that address a multitude of renewable energy types, including solar and photovoltaic, biomass, hydroelectric, and geothermal. The information presented herein is a scientific contribution to energy and environmental regulations, quality and efficiency of energy services, energy supply security, energy market-based approaches, government interventions, and the spread of technological innovation