The research is on compressed air systems by using continuous data monitoring through IOT devices to obtain the data and process which is useful assessing the compressed air system for leak detection, losses in pipe and for performance study. The data can be also used for predictive maintenance and fault detection.
Chintan Lakhani, MS in Mechanical Engineering
Calorimetry of an exothermic reaction is a current of great interest, but requires a high-resolution heat flow measurement. In this work, a fabrication of microwatt resolution ultra-high temperature differential calorimeter studies the heat flow measurement of the reaction between hydrogen and metal hydride. Hydrogen can be stored in different ways; this study focuses on solid-state storage using metal hydride.
Eslam Al Qawasmeh, MS in Mechanical Engineering
This research optimizes latent heat thermal energy storage (LHTES) using triply periodic minimal surface lattices via additive manufacturing. It characterizes the effects of lattice type, density, storage volume, and heat transfer fluid speed on LHTES efficiency. Additionally, it compares LHTES with other energy storage methods based on power output, charge/discharge rates, energy storage density, applications, and limitations. The aim is to enhance LHTES performance and broaden its applicability in energy storage systems.
David Garner, MS in Mechanical Engineering
Blockchain technology’s fully reliable hierarchical ledger capabilities makes it a perfect candidate for alternative technology applications outside of its traditional cryptocurrency use. Here at CAES we are looking into specific use cases for blockchain. More specifically, if the Rutgers microgrid – which includes a roughly 28MW Busch Campus load, a 15MW Cogeneration Plant and 9MW of solar panels – were to act as an island-able, presuming microgrid and sell excess generation. An economic opportunity cost-benefits analysis is being performed as well as how the promotion of renewable energy could increase the value of our green energy. A secondary focus is to calculate and derive the pedigree classification factors which include efficiency, emissions, loss of attributes, reliability and a few other factors of our Rutgers CHP plant. We are hopeful in finding relations that can give us a new pricing model for excess energy to be sold to other plants or back to the grid.
Kelly Baber, MS in Mechanical Engineering
Christopher Murphy, MEng in Energy Systems
Subhash Kungumaraj, MS in Mechanical Engineering
Aditya Mairal, PhD Candidate
The 2023 Distributed Wind Conference (DWEA) took place from February 27th to March 1st 2023 in Washington, DC. This conference is for leaders of the distributed and community wind industry to showcase their sector of the wind industry to an audience of policy makers, agency staff, and renewable energy industry leaders to promote new business opportunities and relationships as well as gain insight into potential new markets. Eslam Al Qawasmeh, David Garner, Evan Bickel, and Dr. Todd Rossi from Rutgers Center for Advanced Energy Systems (CAES) attended the DWEA Conference as part of the REpowering Schools’ (REpS) National Small Wind Turbine Research Project sponsored by FedEx. During the fall semester of 2022, Dr. Todd Rossi merged the research project with the Rutgers mechanical engineering alternative energy course in which 55 senior undergraduate students were introduced to solar, wind and other renewable energy sources; they received hands-on, experiential learning on the fundamentals of wind turbine testing, evaluation, and validation with the small wind turbine donated by REpS. Additionally, CAES will
continue to test the wind turbine in a hybrid wind-solar energy system. At the DWEA Conference, the CAES team presented on the turbine research conducted along with 5 other universities who were part of the REpS program. Students had the chance to network with industry professionals and discuss career opportunities and professional guidance.
Eslam Al Qawasmeh, Graduate Student
Sara Neiss, Graduate Student
Sara Neiss, Graduate Student
The US Energy Information Administration (eia.gov) estimates that demand charges in the commercial sector account for 30 to 70 percent of monthly electric bills, although rates vary considerably by utility, location, season, and building type. One proposed way to curtail high demand charges is by programmatically scheduling flexible loads to even out power consumption over the demand-setting window. The research at Rutgers’ CAES is focused on developing and testing a demand limiting Model Predictive Control (MPC) algorithm for unitary HVAC systems called Unit Coordination (UC). The application coordinates flexible rooftop unit (RTU) loads to avoid coincident runtimes. The MPC algorithm is designed to toggle RTU operation by setting an optimal demand ceiling that forces the zones to “take turns” when flexibility is present. The optimizer can be configured and implemented using only the onsite thermostats, where control decisions are relayed to the thermostats via API as setpoint adjustments that turn units on or off. No physical setup needed. The research explores the scope of viable MPC use cases in Building Energy Management and seeks to uncover real world technical challenges and algorithm deficiencies.
Joshua DeVenezia, Graduate Student
Fluidized beds have enormous potential to improve environmental performance of coal combustion. At CAES, we have studied a wide range of topics related to fluidized bed performance optimization including minimization of temperature fluctuations and the effects of vibration on the system. In addition, we primarily focused on mixing in fluidized beds and breaking up large agglomerates. Designing the size and shape of these objects requires accurate modelling of drag and buoyancy effects, and development of an understanding of the “unfluidized hood” which appears on top of any large submerged object.
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The research is on compressed air systems by using continuous data monitoring through IOT devices to obtain the data and process which is useful assessing the compressed air system for leak detection, losses in pipe and for performance study. The data can be also used for predictive maintenance and fault detection.
Chintan Lakhani, MS in Mechanical Engineering
Calorimetry of an exothermic reaction is a current of great interest, but requires a high-resolution heat flow measurement. In this work, a fabrication of microwatt resolution ultra-high temperature differential calorimeter studies the heat flow measurement of the reaction between hydrogen and metal hydride. Hydrogen can be stored in different ways; this study focuses on solid-state storage using metal hydride.