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Justin E. Elenewski, Gabriela Wojtowicz, Marek Rams, Michael P. Zwolak
Quantum transport simulations require a level of discretization, often achieved through an explicit representation of the electronic reservoirs. These representations should converge to the same continuum limit, though there is a trade-off between a given
Guowen Li, Yangyang Fu, Amanda Pertzborn, Jin Wen, Zheng O'Neill
Energy storage systems have been gaining attention as a means of load management in grid-interactive efficient buildings. This study investigated the physics of the ice storage tank (IST) and implemented an IST model in Modelica. The developed IST Modelica
William Stuart Dols, Chad Milando, Lisa Ng, Steven Emmerich, Jyrteanna Teo
Publicly available tools to perform whole-building simulation of indoor air quality, ventilation, and energy have been available for several decades. Until recently, these tools were developed in isolation of one another. For example, the whole-building
Zhelun Chen, Jin Wen, Anthony J. Kearsley, Amanda Pertzborn
Efficiently, robustly, and accurately solving systems of nonlinear differential algebraic equations (DAE) for dynamic building system simulation is becoming more important due to the increasing demand to simulate large-scale problems including the
Sourav Saha, Orion Kafka, Ye Lu, Cheng Yu, Wing Kam Liu
Design of additively manufactured metallic parts requires computational models that can predict the mechanical response of parts considering the microstructural, manufacturing, and operating conditions. The article discusses the authors' response to Air
Brian Hoskins, Mitchell Fream, Matthew Daniels, Jonathan Goodwill, Advait Madhavan, Jabez J. McClelland, Osama Yousuf, Gina C. Adam, Wen Ma, Muqing Liu, Rasmus Madsen, Martin Lueker-Boden
Building prototypes of heterogeneous hardware systems based on emerging electronic, magnetic, and photonic devices is an increasingly important area of research. On the face of it, the novel implementation of these systems, especially for online learning
Newell Moser, Dohyun Leem, Liao Shuheng, Kornel Ehmann, Jian Cao
Double-Sided Incremental Forming (DSIF) is a rapid-prototyping manufacturing process for metal forming that, for low-volume production, is competitively energy-efficient. However, controlling the DSIF process in terms of accuracy and formability is an
This paper reports on the recently launched zbMATH Links API. We discuss its potential based on the initial link partner, the National Institute of Standards and Technology Digital Library of Mathematical Functions. As the API provides machine readable
Hany Assasa, Nina Grosheva, Tanguy Ropitault, Steve Blandino, Nada T. Golmie, Joerg Widmer
The IEEE Task Group ay (TGay) has recently defined new physical and medium access control specifications to design the next generation wireless standard in the 60 GHz band, the so-called IEEE 802.11ay. Build upon its 802.11ad predecessor, IEEE 802.11ay
Spencer Breiner, Eswaran Subrahmanian, John Dusel, John Foley
As the complexity and heterogeneity of a system grows, the challenge of specifying, documenting and synthesizing correct, machine readable designs increases dramatically. Separation of the system into manageable parts is needed to support analysis at
This work presents the design of an optimal disturbance rejecting tracking controller based on reinforcement learning. The problem involves finding the optimal control parameters that yield asymptotic output tracking in the presence of unmeasurable
Adam J. Kopach, G. F. Nellis, David Bradley, Douglas T. Reindl, Amanda Pertzborn
The Intelligent Building Agents Laboratory (IBAL) at the National Institute of Standards and Technology (NIST) will be used to experimentally study control strategies within the realm of commercial building air-conditioning systems. A TRNSYS [1] model of
We derive all eighteen Gauss hypergeometric representations for the Ferrers function of the second kind, each with a different argument. They are obtained from the eighteen hypergeometric representations of the associated Legendre function of the second
Equilibrium propagation is a learning framework that marks a step forward in the search for a biologically-plausible implementation of deep learning, and could be implemented efficiently in neuromorphic hardware. Previous applications of this framework to