Phase response of the Y2E2 building on the Stanford Campus. This method helped to tune the phasing between the atria temperatures and some of the perimeter offices in an EnergyPlus model.
One Island East – Hong Kong, 70 story sky-scraper. The image illustrates some possible phasing issues in the control system (one zone is heating while the adjacent zone is cooling).
A typical building, with a modern control system, produces about 2 million data points per day (~1500 @ 1 per minute). On the other hand, a building operator or occupant usually has very few questions that they would like answered from this data; is the building comfortable, safe, and clean and is their energy wasted in the operation of the building. In this work, we are looking at ways to aggregate data from building management systems to help answer these simple questions. We use dynamical system tools to calculate the natural and forced modes of the system (using the modes of the Koopman operator). When displaying this information on the backdrop of the architectural plan, it becomes clearly evident where portions of the building either need to be re-tuned or operated differently.
Although we are performing this work on buildings off-campus, we currently focusing our development of these tools on a on-campus building. The Student Resources Building on the UCSB campus is a relatively new construction with many aspects of green building design. It has 60k sq. ft. total, with 13k sq. ft. naturally vent. atrium (many other offices are naturally ventilated). To operate this ventilation strategy, 50 actuated windows at top of Atrium (16 sq.ft. ea.), and 360 sq.ft. actuated louvers on the sides of the building are controlled with digital control systems.
Many of the occupants are uncomfortable during the summer hours because the natural ventilation is not functioning or operating as it should be. Our work will help to make the building more comfortable and to make sure that it is using as little energy as possible.
As building energy modeling becomes more sophisticated, the amount of user input and the number of parameters used to define the models are growing. There are numerous sources of uncertainty in these parameters especially when the modeling process is being performed prior to final construction and commissioning. Past efforts to perform sensitivity and uncertainty analysis have focused on tens of parameters. In this work, we increase the size of analysis by two orders of magnitude (by studying the influence of about 1000 parameters). In addition to this, once uncertainty is quantified in the output of a building model with uncertain input parameters, sensitivity analysis is typically performed to identify which of these input parameters are most influential. We extend this analysis even further to decompose the influence pathway through the dynamics, which identifies which internal or intermediate variables induce the most influence on the output. This work is being performed with United Technologies Research Center and AimDyn, Inc
Model-based optimization is prevalent in many industries from automotive to aerospace engineering. In order to bring building design and engineering up to speed with other industries, model-based optimization is needed. Unfortunately it has been shown that many of the building energy modeling programs that are available to day lack the necessary mathematical properties to allow for this type of optimization (continuity for example). In this work, we use meta-models, which are models of the original model, to perform this optimization. The meta-models that we generate are from the Uncertainty Analysis tasks that is described elsewhere on this website.
Our initial results are very promising in this field and will provide publication links once they are available.
In this work we study the dynamical behavior of a network of multi-stable subsystems. On their own, many physical systems exhibit multiple stable operating points and it is often important to control the dynamics to be near one specific equilibrium (because of various benefits). On the other hand, security, efficiency, and performance are driving engineering designs to be more networked than they have been in the past. When these networks are generated from a series of multi-stable subsystems, the entire network is left with multiple global conformations. Again, each conformation offers different benefits at certain times and therefore a controller is needed to transition between these conformations. Fortunately, instabilities exist in the global dynamics which provide an efficient means to escape from one conformation to another with very little actuation.
In this thesis we draw on tools from dynamical systems and chemical kinetics to qualify and quantify these actuation requirements and other mechanics of this process.As a test-bed for our theory, we study a biologically-inspired chain of bi-stable oscillators which forms a network with two global conformations (a coarse representation of specific DNA dynamics). We investigate re-conformation between these two states and how specific or targeted disturbance influences the transition process. It turns out that strong coupling creates a basis dominated by Fourier modes and the transition process is achieved when resonance allows energy transfer between them.
To better understand this, we derive a multi-phase averaged approximation which illustrates the influence of canonical actions in the Fourier modes. An activation condition is then derived that predicts the minimum activation energy as a function of which Fourier mode is targeted. We also find an unexpected inverse energy cascade which funnels energy from all modes to one coarse coordinate during the activation process. The prediction tools are derived for deterministic dynamics while we also present analogous behavior in the stochastic setting and ultimately a divergence with Kramers rate theory under targeted activation conditions.
I worked in the Systems and Controls group which had a diverse focus including reduced order dynamic modeling, numerical simulation, as well as linear and nonlinear analysis of controlled systems. As UTRC works with all of the business units, I was fortunate to be involved with a diverse set of projects in my tenure their. These projects are summarized below:
My first week at UTRC coincided with a departure of a senior dynamicist at the Fuel Cell business unit. With him went the knowledge of needed to operate a Fortran code of a fuel cell power plant. Myself, and a group of a dozen or so engineers with different backgrounds both at the business unit and a UTRC were tasked with developing a new dynamic model of the system, that was 1) quickly adapted to new system designs, and 2) numerically efficient. We chose Dymola because of its abilities in equation parsing and translation (ie no need for causal modeling), and its DAE solver. The DAEs in this system arise from the multiple feedback of fluidic loops as well as numerous constraints from interconnection of different dynamic systems (note the DAE solver in Dymola was written by L. Petzold, UCSB). We were successful in creating a library containing dynamic models of components that make up a fuel cell. These component could be interconnected using a GUI, translated to create efficient code, and simulated all within a day or so. This was a huge success and had significant impact on the way on the concept of Fuel Cell design.
With a corporate motivation for green products (as well as increasing international pressure through regulation), Carrier was interested in investigating natural refrigerants for their products. Experts at UTRC performed a technical vs. business case trade study and determined that due to the thermophysical properties of natural refrigerants (CO2 for instance) a hot water heat pump would be the most efficient product for market introduction. The use of CO2 however created new control challenges due to the transcritical nature of the cycle. That is, because the cycle traverses the critical point, a new degree of freedom is provided for control. It was my job to design, implement, and test a controller that capitalizes on this. This included investigating many adaptive approaches including both LMS and extremum seeking control, as well as nonlinear feedback control to avoid bifurcations in the system. I was able to work on ~7 patents for this project which was a very useful exercise.
UTC Power, a new business unit, was formed while I was working at UTRC who's focus is to offer power related solutions that spanning many domains. For instance electricity producers from heat (reversed rankine cycle) (product page), or electricity produced from gas (typical microturbine) and cooling and heating produced from the waste heat from these turbines (product page). Total system efficiencies and emissions are targeted in these 'total solutions'. Though the benefits of these integrated solutions are many, they offer technical challenges to the control engineers in charge of integrating them. The challenges are twofold: 1) integration of systems with controllers crossing different platforms and intellectually protected protocols, and 2) new interactions that arise do to the new coupling interactions between the different dynamical systems. To reduce risk when qualifying the functionality of new control algorithms, we used a virtual qualification environment to supplement the experimental testing. Since the time constants of power/heating/cooling and related equipment are very long, dynamic testing takes quiet some time in order to gather information at many operating situations. In addition to this, dynamic testing at edges of the operating envelope (ie dangerous areas) is challenging in the laboratory. A hardware in the loop environment was created to help with these situations. The technical challenges of this effort was to capture enough physics so that the results of the model simulation was accurate, while still being able to integrate in real time. We were able to get enough of the physics of the components (including two phase flows) that was sufficient to match control-oriented data while still solvable in an integration step on dSPACE hardware. These experiments proved to be very helpful as a supplement to the experimental qualification of the new products.
|7||Z. O'Neill and B. Eisenhower Leveraging the Analysis of Parametric Uncertainty for Building Energy Model Calibration Building Simulation Accepted, In press - March 2013||6||B. Eisenhower, Z. O'Neill, S. Narayanan, V. Fonoberov, I. Mezic A Methodology for Meta-Model Based Optimization in Building Energy Models Vol. 47, April 2012 (pdf)|
|5||B. Eisenhower, Z. O'Neill, V. Fonoberov, and Igor Mezic Uncertainty and Sensitivity Decomposition of Building Energy Models Journal of Building Performance Simulation, Vol. 5 No 3, May 2012 (pdf)|
|4||B. Eisenhower, and I. Mezic Targeted Activation in Deterministic and Stochastic Systems Physical Review E, 81, 2, January 2010 (pdf)|
|3||B. Eisenhower, Runolfsson T. System level modeling of a transcritical vapor compression system for bistability analysis Nonlinear Dynamics Volume 55, Numbers 1-2, January, 2009 (pdf)|
|2||B. Eisenhower, G. Hagen, A. Banaszuk and I. Mezic Passive Control of Limit Cycle Oscillations in a Thermoacoustic System Using Asymmetry Journal of Applied Mechanics, Vol 75 No. 1, January 2008 (pdf)|
|1||Mehta, P. G., B. A. Eisenhower Computational Modeling and Analysis of Multiple Steady-States in Vapor Compression Systems ASME Journal of Computational and Nonlinear Dynamics, 2:2, 132:140, April 2007 (pdf)|
|1||B. Eisenhower High Performance Buildings: Measures, Complexity, and Current Trends Cities for Smart Environmental and Energy Futures Springer Verlag (expected printing early 2013)|
|Refereed Conference Papers||18||C. Bhamornsiri, P. Gomez, T. Wilson, and B. Eisenhower Calibration of Envelope Parameters using Control-Based Heat Balance Identification and Uncertainty Analysis International Building Performance Simulation Association, BuildSim 2013, France.|
|17||B. Eisenhower and I. Mezic Uncertainty in the Energy Dynamics of Commercial Office Buildings 2012 IEEE 51st Annual Conference on Decision and Control, 2012 (pdf) [Invited session organizer]|
|16||Z. O’Neill, B. Eisenhower, V. Fonoberov and T. Bailey. Calibration of a Building Energy Model Considering Parametric Uncertainty ASHRAE Transactions, 118(2). ASHRAE Annual Meeting. San Antonio, TX. Jun 23–27, 2012.|
|15||M. Georgescu, B. Eisenhower, and I. Mezic Creating zoning approximations to building energy models using the Koopman Operator IBPSA-USA's SimBuild 2012 Conference The Future of Simulation for Buildings (pdf)|
|14||K. Otto, B. Eisenhower, Z. O'neill, I. Mezic, and S. Narayanan Prioritizing Building System Energy Failure Modes Using Whole Building Energy Simulation IBPSA-USA's SimBuild 2012 Conference The Future of Simulation for Buildings(pdf)|
|13||B. Eisenhower, K. Gasljevic, and I. Mezic Control-oriented dynamic modeling and calibration of a campus theater using Modelica IBPSA-USA's SimBuild 2012 Conference The Future of Simulation for Buildings (pdf)|
|12||B. Eisenhower, V. Fonoberov, and I. Mezic Uncertainty-weighted Meta-model Optimization in Building Energy Models IBPSA-England 1st Conference on Building Simulation and Optimization (BSO12) (pdf) [Best paper at the conference award]|
|11||B. Eisenhower and I. Mezic Extracting Dynamic Information from Whole-Building Energy Models Proceedings of Conference on Dynamics for Design, AMSE August 12-15, 2012, Chicago, IL, USA (pdf)|
|10||B. Eisenhower, Z. O'Neill, S. Narayanan, V. Fonoberov, and I. Mezic A Comparative Study on Uncertainty Propagation in High Performance Building Design International Building Performance Simulation Association, BuildSim 2011, Australia (pdf)|
|9||Z. O'Neill, B. Eisenhower, S. Yuan, T. Bailey, S. Narayanan, V. Fonoberov Modeling and Calibration of Energy Models for a DoD Building, ASHRAE Transactions, Volume 117, Part 2, 2011 (pdf)|
|8||B. Eisenhower, T. Maile, M. Fisher, and I. Mezic Decomposing Building System Data for Model Validation and Analysis using the Koopman Operator IBPSA National Conference, Simbuild, NY August 2010 (pdf)|
|7||B. Eisenhower and I. Mezic Actuation Requirements in High Dimensional Oscillator Systems Proceedings of the 2008 American Control Conference, Seattle June 2008 (pdf)|
|6||B. Eisenhower and I. Mezic A mechanism leading to conformation change in networked nonlinear systems Proceedings of the 46th IEEE Conference on Decision and Control, New Orleans December 2007 (pdf) [Invited session chair]|
|5||B. Eisenhower and T. Runolfsson Control Analysis of Bistable Behavior in a Transcritical Heat Pump Proceedings of the 44th IEEE Conference on Decision and Control, Paradise Island December 2004 (pdf)|
|4||M. A. Vaudrey, W. R. Saunders, B. Eisenhower Test Based Methodology for Apriori Selection of Gain/Phase Relationships in Proportional, Phase-Shifting Control of Combustion Instabilities Proceedings of ASME Turbo Expo: Munich, Germany May 2000. ASME Paper 2000-GT-0530 (pdf, pg.1 )|
|3||W. R. Saunders, M. A. Vaudrey, B. Eisenhower, U. Vandsburger Perspectives on Linear Compensator Designs for Active Combustion Control AIAA Paper 99-0717, 1999 (pdf, pg.1 )|
|2||C. A. Fannin, W. R. Saunders, M. A. Vaudrey, B. Eisenhower, U. Vandsburger Analytical and Practical Considerations for Control of Thermoacoustic Instabilities AIAA Paper 99-0718, 1999 (pdf, pg.1 )|
|1||W. R. Saunders, B. Eisenhower, [and 7 other authors] Diagnostics and modeling of acoustic signatures in a tube combustor 6th International Congress on Sound and Vibration. 1999: Lyngby, Denmark. p. 3377-3384 (pdf)|
|Invited Lectures and Un-refereed Conferences or Articles|
|16||B. Eisenhower Uncertainty management in whole-building energy models, AHSRAE and IBPSA Joint meeting (Los Angeles), November 2012, (slides) [Invited speaker]|
|15||B. Eisenhower High Performance Buildings: Measures, Complexity, and Current Trends, International Center for Materials Research, Summer School on Inorganic Materials for Energy Conversion and Storage, August 2012 [Invited speaker]|
|14||B. Eisenhower Applied Mathematics at the Forefront of Energy Efficiency in Buildings, SIAM News Vol 45, No. 6, July/Aug 2012, (Archived @ SIAM)|
|13||B. Eisenhower Model-based Building Design Considering Uncertainty, IBPSA-USA's SimBuild 2012 Conference The Future of Simulation for Buildings, (slides) [Invited semi-plenary speaker]|
|12||B. Eisenhower Recent advances in tools for energy efficient building design and operation, American Planning Association - California Chapter Meeting, June 2012|
|11||B. Eisenhower An integrated approach to design and operation of buildings in the presence of uncertainty, The First Society of Applied Mathematics Conference on Uncertainty Quantification, Raleigh NC, 2012 (slides) [Session organizer and chair]|
|10||B. Eisenhower An integrated framework for parametric design using building energy models, United Technologies Research Center, Invited Honoraria Speaker, August 2011 (pdf slides)|
|9||B. Eisenhower Uncertainty and Sensitivity Analysis in Building Energy Models, 2011 SIAM Conference on Applications of Dynamical Systems, Snowbird UT(pdf slides) [Session organizer and chair]|
|8||B. Eisenhower Decomposition of uncertainty propagation through networks of heterogeneous energy systems, 2011 Focus Period on Dynamics, Control and Pricing in Power Systems. Lund University, Sweden(pdf slides) [Invited participant]|
|7||B. Eisenhower Dissecting the Complex Dynamics of Operational Building Data and their Simulation Models International Workshop on Smart Energy Management. Kyoto, Japan. Spring 2010(pdf slides) [Invited participant]|
|6||B. Eisenhower Targeted Escape in Large Oscillator Networks UC Berkeley Department of Mechanical Engineering - Visiting Speaker, Fall 2009 (pdf slides)|
|5||B. Eisenhower Deterministic Activation in Coupled Oscillator Arrays 2009 SIAM Conference on Applications of Dynamical Systems, Snowbird UT (pdf slides) [Session chair]|
|4||B. Eisenhower and I. Mezic Internal Dynamics and Coordinated Behavior in Nonlinear Interconnected Systems AFOSR Complex Networks Workshop, Arlington VA, Feb 2008 (pdf slides)|
|3||B. Eisenhower Mechanisms Driving Conformal Arrangements, DARPA Program Review, Key West Florida, Fall 2007(pdf slides)|
|2||B. Eisenhower Targeted Activation in Coupled Multi-stable Systems 2008 Dynamics Days, Knoxville TN (pdf poster)|
|1||B. Eisenhower Stability of Coupled Pendula 2007 SIAM Conference on Applications of Dynamical Systems, Snowbird UT (pdf slides) [Session organizer and chair]|
|10||I. Mezic and B. Eisenhower Method for Energy Efficient Building Design and Management In Process|
|9||B. Eisenhower, C. Park, P. Kang, A.M. Finn, T.H. Sienel Supercritical Pressure Regulation of a Vapor Compression System by Adaptive Control US 6,813,895|
|8||B. Eisenhower Non-linear control algorithm in vapor compression systems US 7,171,820|
|7||B. Eisenhower and J. I. Concha Vapor compression system startup method US 7,127,905|
|6||T. Sienel, Y. Chen, B. Eisenhower, et al. Method of controlling a carbon dioxide heat pump water heating system US 7,010,925|
|5||J. Concha, T. Sienel, B. Eisenhower, Energy-efficient heat pump water heater US 7,225,629|
|4||B. Eisenhower and J. Concha Multivariable control of refrigerant systems US 6,993,921|
|3||J. Concha, T. Sienel, B. Eisenhower, and Y. Chen Pressure regulation in a transcritical refrigerant cycle US 7,389,648|
|2||B. Eisenhower, T. Sienel, N. Pondique-Casou Sanitary Operation of a Hot Water Heat Pump filed September 1, 2003 (CA-DN 11015, UTRC R-05253)|
|1||L. Pedersen,B. Eisenhower,J. Isom, and U. Vaidya Charge Loss Detection Using Receiver Temperature Measurements In progress at Business Unit|
|B. Eisenhower Targeted Escape of Large Oscillator Networks May 2009. Committee: Igor Mezic, Jeff Moehlis, Karl Astrom, and Andrzej Banaszuk (pdf slides),(pdf dissertation)|