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On-going Projects: 

1)     Title: EEB-HUB Task 4.3 Whole Building Diagnostic and Decision Support Systems for Energy Efficient Operation and Cost Effective Services

PI: Jin Wen

Research Assistant: Adam Regnier

Collaborators: Purdue University and United Technology Research Center

Funding Agency: US DOE Energy Efficient Building Hub (http://www.eebhub.org/)

Duration: 2010 – 2015

Description: This project will develop and demonstrate a library of diagnostics decision support tools that can enable cost effective diagnostics solutions for existing buildings.  Whole building diagnostic and decision support tools should robustly maintain building energy performance at an optimal level following commissioning of retrofitted buildings. Drexel University will work closely with Purdue and UTRC teams and will a) Identify building mechanical system and fault types that have the strongest energy impact; b) Develop a user friendly virtual testbed for a small commercial building that is equipped with a single duct AHU-VAV system.  The testbed is able to simulate both fault free and faulty system operations and is able to communicate with real building control systems.  The testbed will be developed based on the simulation models developed from ASHRAE Research Project 1312 (PI: J. Wen), which have been experimentally validated at both component level and system level.  c) Develop and evaluate a dynamic fault detection and diagnosis prototype for a single duct AHU-VAV system.  The prototype includes existing algorithms developed by the Drexel team that combines Principle Component Analysis technique, Wavelet Transform technique, and Pattern Matching technique.  The prototype will be evaluated using fault experimental data collected by the Drexel team, as well as using the developed virtual testbed. And d)  demonstrate the developed AHU-VAV diagnostics tools in identified real buildings.


2)    Title: Tools for Evaluating Fault Detection and Diagnostic Methods for HVAC Secondary Systems of a Net Zero Building

PI: Jin Wen

Research Assistant: Shokouh Poorarian and Xiwang Li

Collaborators: Iowa Energy Center Energy Resource Station

Funding Agency: the National Institute of Standard Technology

Duration: 2010 – 2013

Description: Secondary systems, such as fan coil units, fan power units, and dual duct systems, although widely used in commercial, industrial, and multifamily residential buildings, have received very little attention in terms of improving their system performance.  This project proposes to develop tools that provide simulation environments to develop and evaluate advanced control, operation, and fault diagnosis technologies for these less studied secondary systems.  More specifically, this project aims at

·          Developing dynamic simulation models in the HVACSIM+ environment for common fan coil unit, fan power unit, and dual duct system configurations.  The developed simulation models shall be able to produce both fault-free and faulty operational data under a wide variety of faults and severity levels for advanced control, operation, and fault diagnosis technology development and evaluation purposes;

·          Developing a model structure, which includes the grouping of blocks and superblocks, treatment of state variables, initial and boundary conditions, and selection of equation solver, that can simulate a dual duct system efficiently with satisfactory stability;

·          Identifying, collect, and analyze existing experimental data that can be used to validate the developed simulation models;

·          Designing and conduct a comprehensive and systematic validation procedure using collected experimental data to validate the developed simulation models under both fault-free and faulty operational conditions; and

·          Developing an efficient user interface and database to collect and store building and system parameters.



       Title: CPS: Synergy: Collaborative Research: SMARTER - Smart Manager for Adaptive and Real-Time decisions in building clustERs

PI (Drexel Team): Jin Wen

Research Assistant: Xiwang Li

Collaborators: Arizona State University (PI: Teresa Wu); University of Buffalo (Kemper Lewis)

Funding Agency: National Science Foundation

Duration: 2012 – 2015

Description: In this project, we propose a new concept: NetZero energy building clusters. Our objective is to develop a synergistic decision framework to enable such next-generation building clusters to work as an adaptive and robust system within a smart grid, reducing overall energy consumption and allowing for optimal operation decisions enabled by cyber support tools. Our vision is that the next generation building systems will freely form clusters, within each of which buildings can autonomously share and exchange site-generated energy, fundamentally transforming the consumption of energy in buildings, which comprises the largest sector of energy consumption. The primary research challenges are:  a) Develop an emulator for NetZero energy building clusters to benchmark and evaluate different operation strategies; b) Develop and calibrate networked energy consumption models for temporally and spatially distributed buildings, and c) Develop multi-time scale adaptive decision algorithms for dynamic operation strategies. The intellectual merit of this proposal lies in developing innovative algorithms and tools in four disciplines (building energy modeling, intelligent data fusion, decentralized decision and adaptive Pareto decisions) as well as providing the synergy for their unique seamless integration to address the theoretical and practical challenges in next-generation building systems. The primary research issues that constitute the significant intellectual challenges include developing automatous self-tuned high-fidelity models for building systems, advancing noise-tolerant techniques in data fusion for multi-model calibration, studying Pareto optimality in multi-time scale decentralized decisions, and developing methods to determine the optimal trajectory of changes in adaptive decisions. Not only will we address the critical issues in each discipline, but we will also provide an interdisciplinary framework to support the intelligent design and emergence of next-generation NetZero building clusters. The intellectual contributions will result in a transformation from the current centralized and unidirectional power distribution model in the energy industry to a decentralized and multi-directional power sharing and distribution model.


Completed Projects


1)    Title: ASHRAE 1312-RP Tools for Evaluating Fault Detection and Diagnostic Methods for Air-Handling Units

PI: Jin Wen

Research Assistant: Shun Li

Collaborators: Iowa Energy Center Energy Resource Station

Funding Agency: ASHRAE

Duration: 2006-2011

Description:  An air handling unit (AHU) connects primary heating and cooling plants with building zones, controls building ventilation air intake, and greatly affects the energy consumed for heating, cooling, and ventilating, as well as supply air temperature and humidity levels.  An AHU's operation significantly impacts building energy use, health, and comfort aspects.  A dynamic AHU simulation model that is capable of producing operational data for commonly used AHU configurations will assist further research in AHU control and operation, as well as fault detection and diagnosis. 

                In this study, dynamic behaviors of an AHU and four building zones that are served by the AHU are modeled using HVACSIM+ software developed by the National Institute of Standards and Technology.  The model (called 1312 model hereafter) is developed based on two previous ASHRAE projects (RP 825 and RP 1194).  However, significant modifications, including new parameters, control strategies, and component models, which are a new coil valve model and a new fan energy model, are developed in this study to ensure that the 1312 model simulates the dynamic behavior of the systems in the test facility.  The new coil valve model considers nonlinear behaviors of a three way valve.  The new fan energy model outputs fan energy consumption that includes energy consumptions for fan, belt, motor and VFD.  Coefficients for the new fan energy model can directly be estimated from the total fan energy measurement.

               The developed 1312 AHU model is then systematically validated using experimental data for both fault free and faulty operation.  Strategies to validate the model using experimental data mostly from common system operations are designed.  If problems were identified using system operation data, follow up component model calibration is used to modify and improve the model.  A series of experiments are designed and implemented to obtain pressure resistance parameters for the supply duct system and mixing box dampers.  Building operation data from winter, summer, and spring seasons are used to validate the 1312 model.  Good agreements are achieved between experimental data and simulation outputs for the 1312 AHU model, especially for summer and winter seasons.  When using 1312 model to simulate AHU operation for spring season conditions, simulated outdoor and supply air flow rates and supply air temperature, while tracking experimental data, showed certain level of oscillation. 

                Common AHU faults, including their features and severities, are identified in this project.  Existing experimental data that can be used to validate the 1312 AHU model under fault free and faulty operation conditions are collected.  Additional experiments are performed to thoroughly validate the 1312 AHU model under both fault free and faulty operation conditions.  The fault models are able to replicate all major fault symptoms although detailed dynamics between simulated data and measured data do not always overlap. 


2)   Title: ASHRAE 1353-TRP Stability and Accuracy of VAV Box Control at Low Flows

PI: Jin Wen

Research Assistant: Ran Liu and Adam Regnier

Collaborators: Iowa Energy Center Energy Resource Station

Funding Agency: ASHRAE

Duration: 2007-2011

Description:           Variable air volume (VAV) systems with direct digital controllers (DDC) have been widely adopted in HVAC systems of commercial, industrial, and large residential buildings, because they provide better energy efficiency and occupant comfort.  Normally, a VAV terminal unit defines a minimum airflow rate to satisfy the space ventilation requirement and/or the proper operation of a terminal heating coil, if so equipped.  However, if the embedded airflow sensor becomes inaccurate, and the designed minimum airflow rate is less than the minimum controllable airflow rate, then a series of problems could happen, such as a lack of ventilation, uneven control of airflow, reduced damper and operator life, and energy waste.  This study aims at identifying the strong factors and the relationship between the strong factors and the performance of the airflow sensor (e.g. flow probe provided with the VAV box), controller (e.g. differential pressure transducer included in a VAV box controller, and the data acquisition and control algorithms included in the controller), and terminal unit system (e.g. flow probe plus transducer/data acquisition plus control algorithm) through systematically designed laboratory and field tests.


       Title: Framework for Assessing the Energy Efficiency Strategies of the Philadelphia Housing Authority

PI: Jin Wen and Patrick Gurian

Research Assistant: Liam Hendricken, Jared Langevin, Ran Liu and Adam Regnier

Funding Agency: Philadelphia Housing Authority

Duration: 2010-2012

Description: The overall objective of this project is to develop a framework to evaluate, assess and promote energy efficiency and alternative energy strategies for PHA with multifamily housing portfolios though energy simulation, energy measurement, energy performance assessment, cost-benefit analysis, and energy policy studies.

More specifically, the scope of this project includes:

a.   Develop a cost-benefit analysis framework (methods and tools) to assess energy strategies and to make decisions under uncertainties;

b.   Develop an energy assessment measurement and verification (M&V) framework to measure and verify energy savings from energy conservation methods; 

c.   Develop Energy Plus (E+) models for selected stimulus project buildings (Markoe Street 23 unit development, Plymouth Hall redevelopment, Mantua Hall Redevelopment, and Paschall Redevelopment) and one existing building (Harrison Plaza high rise building);

d.   Develop a model validation methodology and perform limited scale model validation practice for the Harrison Plaza high rise building model;

e.   Collect occupant behavior data to understand and incentivize energy efficient behaviors.


          Title: Fellowship Program in Microbial Risk Assessment for Built Environment Integrated Academic/Employment Opportunities at the Center for Advancing Microbial Risk Assessment

PI: Jin Wen, Patrick Gurian, and C. N. Haas

Supported MRABE Fellow: Ian Solon, Kyle Griffith, Liam Hendricken, Alex Bui

Funding Agency: Department of Homeland Security

Duration: 2008-2012

Description: With support from the Department of Homeland Security, Drexel University designed and offered a fellowship program in Microbial Risk Assessment for Built Environment (MRABE). The fellowship program integrated 1) academic coursework at Drexel University, 2) research at the Center for Advancing Microbial Risk Assessment, a Drexel-based Environmental Protection Agency and Department of Homeland Security Research Center of Excellence, and 3) two, 6-month professional internships at Homeland Security Science Technology Engineering Mathematics (HS-STEM) sites. Four MRABE Fellows were recruited and trained in this program. 


       Title: A Smart Indoor Air Quality Sensor Network

PI: Jin Wen

Research Assistant: Lisa Chen Ng

Funding Agency: National Science Foundation

Duration: 2005-2006

Description: This project aims at designing and implementing a smart indoor air quality (IAQ) sensor system in a real demonstration building. The proposed IAQ sensor network consists of sensors that supply long term continuous measurements for indoor gas pollutants, particle pollutants, and bio-aerosol pollutants. The design and evaluation methodologies for a comprehensive IAQ sensor network are explored. The data collection and analysis methods are examined. The innovation of the proposed study include: 1) systematically examine how to design and evaluate the next generation comprehensive IAQ sensor network; and 2) construction and implementation of a smart IAQ sensor network which includes large variety of IAQ sensors in a real building to supply long-term real time IAQ measurements for the relevant research society and to demonstrate the next generation IAQ sensor network concept.


        Title: REU Site: SENSORS - Design to Implementation

PI: Caroline Schauer and Jin Wen

Funding Agency: National Science Foundation

Duration: 2006-2013

Description: The objective of this REU proposal is to provide the selected REU participants with a rare research opportunity, exposing them to the entire exploration process of creating a viable sensor and sensor network for various real-life applications. Hands-on research activities, a multi-disciplinary working environment, systematic research education, strong industrial connections, and comprehensive ethics activities are designed to increase the participants' knowledge and interest in research and sensor technology from design to implementation, as well as instill a strong desire to continue with research at the graduate level. The project includes a wide range of faculty from the entire Engineer College as well as Medical School as senior investigators. 


       Title: Flexible Floor Plans – A Modular, Reconfigurable, & Sustainable Floor & Wall System

PI: Jin Wen and Eugenia Ellis

Funding Agency: Green Building Alliances

Duration: 2006-2008

Description: A modular wall and floor system that is sustainable and appropriate for residential settings will be designed and experimentally tested in this project.  Existing building constructions do not allow their occupants to easily reconfigure the floor plans, even though peoples’ needs constantly change during their lifetime.  People often have to either renovate their houses or to move to a larger one.  Large quantities of material and energy are wasted during a renovation process because old wall and floor materials are difficult to be reused.   Research studies have demonstrated that modular wall and floor systems can provide flexible floor planning, better indoor air quality, and improved energy efficiency.  In this project, scientific approaches including theoretical simulation, prototype construction and testing, as well as life-cycle analysis, will be adopted to design and test an innovative modular wall and floor system for residential buildings.  More specifically, the proposed system will 1) be lightweight and reconfigurable by regular residential occupants; 2) allow customized finishing materials; 3) be soundproof; and 4) maximize the usage of local materials to achieve a more sustainable solution.  The final deliverables include a prototype modular wall and floor system, final report, user manual, and design guidance.