A Mathematical Framework for Increasing Trust in Human Machine Interactions
The objective of the proposed research is to mathematically characterize the dynamic relationship between machine user interfaces (UIs) and human trust in automated systems. With increasing automation in all aspects of society, humans are increasingly being displaced as the primary decision-maker in roles such as aircraft pilots and plant operators. However, humans still have the ability to override automated decisions, and a significant problem arises when humans override an automated decision due to a fundamental lack of trust in the machine. Two specific aims guide this research. The first aim is to conduct a dynamical characterization of real-time measurements of trust. Such measurements do not currently exist and are necessary in order to allow machines to sense the trust level of the humans that they are interacting with.
We propose to identify a dynamic model of trust that relies on real-time psychophysiological measurements such as galvanic skin response (GSR) and electroencephalography (EEG), as well as eye-tracking and facial expression. The second aim is to define a mathematical framework for modelling human emotional response to machines. Machines communicate with humans through various design features in their user interface (UI). We propose to conduct a human subjects study to mathematically characterize how specific machine UI features can be used by a machine to dynamically change human trust in the machine. Through the proposed research, we will enable the design of a closed-loop emotional intelligence system that achieves the overarching goal of improving the relationship between human and machine, thereby leading to more reliable and efficient operation of a range of automated systems.Sponsor: NSF Award No. 1548616
Advanced Caster Roll Gap Control
According to the World Steel Association, in 2014, 1.7 billion tons of steel were produced worldwide; the United States alone produced 240 thousand tons of crude steel each day. Steel strip is used in applications ranging from building construction to automobile manufacturing. Twin roller casting produces steel strips by pouring steel directly onto rollers and compressing it to a thickness near the final gauge, whereas traditional casting uses a mold to form a steel slab that is later rolled to the desired thickness. The twin roller method is 9 times more energy efficient and 7000 times faster than thick slab casting. However, achieving precise physical properties along the length of the strip poses a challenging engineering problem due to the highly coupled nature of the thermal and mechanical dynamics.
A model of the coupled dynamics can yield insights into the appropriate control architecture and methodology that will overcome performance limitations levied by system characteristics such as time delays and unmeasurable variables. The development of a control methodology for highly-coupled and high frequency thermal and mechanical dynamics will not only improve the quality of the steel produced by the twin roll casting process but will also translate to other materials processing and manufacturing applications.
Sponsor: Castrip LLC
Dynamic Modeling, Control, and Optimization of micro-CHP Systems
Around the world, there is a growing penetration of distributed energy resources (DERs) into the power generation landscape. Blackouts continue to cause major disruptions in many countries, including the U.S., but a more distributed energy generation landscape can offer more robustness to these types of failures. From an efficiency standpoint, transmission losses can be minimized by generating and consuming electricity at the same location through an increase in the use of DERs. Micro-combined heat and power systems (micro-CHPs) are especially useful as DERs because unlike renewables, micro-CHPs can be directly controlled. While CHP has been traditionally used in the industrial and commercial sectors, micro-CHP systems typically produce less than 5kW of electricity and are primarily aimed at the residential and small building market to meet electricity and domestic hot water needs.
A major challenge with the use of micro-CHP systems concerns reconciling synchronous generation of electricity and heat with asynchronous demand. In this research we will first model and study the relationship between energy storage dynamics (specifically sensible thermal storage) and those of a prime mover (specifically a PEM fuel cell) to understand how storage sizing affects system bandwidth. This analysis will then guide the design of optimal control strategies to meet time-varying, and asynchronous, electricity and heating demands. The use of second law based metrics for characterizing efficiency of the micro-CHP system will be a critical aspect of the optimization problem formulation.
Optimal Plant and Control Co-Design for Thermal Energy Systems
Thermal management systems are often designed using steady-state analysis with a worst-case scenario in mind. For example, components are designed to accommodate maximum expected heat loads. Unfortunately, by designing systems in this manner, closed-loop transient performance is both overlooked and limited. Instead, it is imperative that transient component modeling and subsystem interactions be considered at the design stage to avoid costly future redesigns. As the need for MW-scale cooling rises for many systems, the importance of optimal thermal management increases. Simply put, there exists a critical need for new design strategies to realize the full potential of thermal management systems.
This need can be addressed through the use of combined plant and control design, or co-design. Co-design is a process wherein a system’s governing control policy, and thus its closed-loop performance, is considered at the plant design stage. The merits of co-design are rooted in the fact that there are fundamental limitations to what can be achieved with the addition of feedback control for a given plant design. In the past, the concept of co-design has been largely used in the aerospace and mechanical engineering communities. However, co-design has untapped potential in the realm of thermal management systems. As such, this research will explore optimal design of thermal systems by considering closed-loop performance at the design stage through the use and development of co-design algorithms.
Sponsor: Office of Naval Research
Optimizing Residential Air-Conditioning Equipment for Demand Responsiveness, Energy Efficiency, and Environmental Impact
Air conditioning (A/C) use is one of the primary causes of high electricity demand, particularly in hot climates. Utility companies have started to introduce variable electricity pricing for residential consumers in an attempt to create a shift in load demand from the peak hours. The integration of a secondary loop and thermal storage can give air conditioning units the ability to reduce this demand during peak pricing hours. This project will assess the benefits of the inclusion of thermal energy storage, natural refrigerants, and energy recovery technologies into packaged residential A/C units. A dynamic model will be developed to optimize the system design and its energy management strategy based on multiple objectives, including cost, efficiency, and demand responsiveness.
Sponsor: Center for High Performance Buildings
Powering What’s Next in Freight Transportation
Ana Isabel Guerrero de la Peña
The future of freight transportation seems to be changing dramatically. It is easy to envision this future simply as a number of autonomous transportation systems, but future concepts in transportation and logistics will likely take the form of connected and collaborative systems-of-systems (SoS), each system with optimized levels of autonomy. Current and future trends show that trucks carry a majority of the load of freight transportation, and therefore, the future of internal combustion engines and the role they play in powering these systems poses an equally important question.
The following concepts will be analyzed through the development of a mathematical simulation model for connected and collaborative system-of-systems: the correct network topology and interaction of resources for optimal performance and safety of freight transportation, the level of vehicle autonomy and the implications on infrastructure and operation, anticipation of driver behavior and effect on vehicle operation, and finally, the vehicle powertrain system design that will provide an efficient, cost effective, and environmentally friendly propulsion mode for the given SoS concept.
Sponsor: Cummins, Inc.