Christopher's interests lie in the intersection of the modeling of physical systems and the experimental construction and testing of these systems, including simulation, numerical methods, and fault detection. He has worked on a variety of multi-physical systems, such as thermo-fluid systems and electromechanical energy conversion systems.
Where: American Control Conference (ACC)
MERL Contacts: Mouhacine Benosman; Scott Bortoff; Petros Boufounos; Daniel Burns; Claus Danielson; Stefano Di Cairano; Amir-massoud Farahmand; Abraham Goldsmith; Piyush Grover; Uros Kalabic; Andrew Knyazev; Christopher Laughman; Daniel Nikovski; Arvind Raghunathan; Yebin Wang; Avishai Weiss
Research Areas: Multimedia, Data Analytics, Mechatronics, Business Innovation, Advanced Control Systems, Dynamical Systems, Machine Learning, Predictive ModelingBrief
Date: July 6, 2016 - July 8, 2016
- The premier American Control Conference (ACC) takes place in Boston July 6-8. This year MERL researchers will present a record 20 papers(!) at ACC, with several contributions, especially in autonomous vehicle path planning and in Model Predictive Control (MPC) theory and applications, including manufacturing machines, electric motors, satellite station keeping, and HVAC. Other important themes developed in MERL's presentations concern adaptation, learning, and optimization in control systems.
Where: University of Connecticut
MERL Contacts: Christopher Laughman; Scott Bortoff; Hongtao Qiao
Research Area: Data AnalyticsBrief
Date: November 11, 2015 - November 12, 2015
- MERL Researchers Scott A. Bortoff, Chris Laughman and Hongtao Qiao attended the North America Modelica User's Group Meeting, hosted by the University of Connecticut, November 11-12, 2015. Scott Bortoff gave the Keynote Address entitled "Using Modelica in Industrial Research and Development," and Chris Laughman and Hongtao Qiao each presented a paper on modelling of HVAC systems. The Meeting attracted approximately 80 Modelica users from a diverse set of companies and universities including United Technologies, Johnson Controls and Ford. Use of Modelica is accelerating in North America, lead by largely by automotive and similar "systems manufacturing" type companies.
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BI1163: Multiphysics simulation and optimization
MERL is seeking a motivated graduate student to research numerical methods related to model-based simulation and optimization for process applications. Representative targets include the fast simulation of multiphase flows and the optimization of nonsmooth systems found in energy applications. The ideal candidate would have a solid background in numerical methods, partial differential equations, and optimization; strong programming skills and experience with Python/C++/Matlab are also expected. Knowledge of the fundamental physics of thermofluid flows (e.g., thermodynamics, heat transfer, and fluid mechanics), nonlinear dynamics and control methods, or Modelica or other equation-oriented languages (gPROMS, Aspen HYSYS, extensions to Julia such as JuMP.jl) is a plus. The expected duration of this internship is 3 months. Please contact Chris Laughman (laughman at merl.com) or go to www.merl.com/internship/ for more information.
- "Optimization of circuitry arrangements for heat exchangers using derivative-free optimization", Chemical Engineering Research and Design, DOI: 10.1016/j.cherd.2017.05.015, October 2017. ,
- "Simulation and Optimization of Integrated Air-Conditioning and Ventilation Systems", International Building Performance Simulation Association Conference, August 2017. ,
- "Dynamic Characteristics of an R-410A Multi-split Variable Refrigerant Flow Air-conditioning System", 12th IEA Heat Pump Conference, May 2017. ,
- "On the Influence of State Selection on Mass Conservation in Dynamic Vapor Compression Cycle Models", Mathematical and Computer Modeling of Dynamical Systems, DOI: 10.1080/13873954.2017.1298625, Vol. 23, No. 3, pp. 262-283, December 2016. ,
- "Kernel Regression for the Approximation of Heat Transfer Coefficients", Gustav Lorentzen Natural Working Fluids Conference, August 2016. ,
Title: "System and Method for Controlling of Vapor Compression System"
Inventors: Burns, Dan J; Jain, Neera; Laughman, Christopher; Di Cairano, Stefano; Bortoff, Scott A.
Patent No.: 9,625,196
Issue Date: Apr 18, 2017
Title: "Method For Reconstructing 3D Scenes From 2D Images"
Inventors: Ramalingam, Srikumar; Taguchi, Yuichi; Pillai, Jaishanker K; Burns, Dan J; Laughman, Christopher
Patent No.: 9,595,134
Issue Date: Mar 14, 2017
Title: "System and Method for Controlling Vapor Compression Systems"
Inventors: Burns, Dan J; Laughman, Christopher; Bortoff, Scott A.
Patent No.: 9,534,820
Issue Date: Jan 3, 2017
Title: "System and Method for Controlling Temperature and Humidity in Multiple Spaces using Liquid Desiccant"
Inventors: Laughman, Christopher; Burns, Dan J; Bortoff, Scott A.; Waters, Richard C.
Patent No.: 9,518,765
Issue Date: Dec 13, 2016
Title: "Adaptive Control of Vapor Compression System"
Inventors: Burns, Dan J; Laughman, Christopher
Patent No.: 9,182,154
Issue Date: Nov 10, 2015
Title: "Controlling Operation of Vapor Compression System"
Inventors: Nikovski, Daniel N.; Laughman, Christopher; Burns, Dan J
Patent No.: 8,793,003
Issue Date: Jul 29, 2014
Title: "System and Method for Controlling Operations of Vapor Compression"
Inventors: Bortoff, Scott A.; Burns, Dan J; Laughman, Christopher
Patent No.: 8,694,131
Issue Date: Apr 8, 2014
- Title: "System and Method for Controlling of Vapor Compression System"