Experimental Investigation and Data-Driven Modeling for Variable Refrigerant Systems
by Po-Ching Hsu
Variable refrigerant flow (VRF) systems have gained widespread adoption in commercial and residential buildings due to their high part-load efficiency, zoning flexibility, and superior thermal comfort performance. As buildings account for a substantial portion of global energy consumption and carbon emissions, improving the modeling, control, and operational efficiency of VRF systems has become increasingly important. However, the growing structural and operational complexity of modern VRF systems, characterized by variable-speed compressors, multiple indoor units, electronic expansion valves, and heat recovery configurations, poses significant challenges for accurate system modeling and advanced control implementation. Traditional curve-based models, while computationally efficient and physically interpretable, often lack sufficient control-oriented inputs and struggle to capture transient dynamics. Conversely, purely data-driven models demonstrate strong predictive performance but may suffer from limited physical consistency, robustness, and generalizability. These limitations highlight the need for a hybrid modeling framework that combines the strengths of both approaches.
This dissertation presents a comprehensive experimental and modeling investigation of VRF systems based on long-term field test data. A multi-functional VRF (MFVRF) system installed in a campus office building was instrumented to capture detailed operational data across diverse seasonal and operating conditions. The resulting database enabled exploratory analysis of system behavior, part-load performance, and the impact of control strategies on energy consumption and thermal comfort.
Building on this dataset, multiple data-driven models were developed to capture VRF system behavior, including decision trees (DTs), artificial neural networks (ANNs), and long short-term memory (LSTMs). A systematic evaluation framework was established to assess predictive accuracy, physical consistency, computational efficiency, and model compactness. Results demonstrate that deep learning models, particularly LSTM-based architectures, effectively capture transient and nonlinear system behavior, achieving higher predictive accuracy than shallow machine learning (ML) models. To enhance robustness and physical interpretability, a hybrid modeling framework was proposed by integrating a modified VRF-SysCurve physics-based model with ML models such as ANN. The hybrid structure preserves key thermodynamic relationships while incorporating control-oriented variables, enabling improved predictive accuracy and greater flexibility for control applications. Transfer learning strategies were implemented to fine-tune sub-models for underrepresented indoor units using limited additional data, thereby improving generalizability and data efficiency. Compared with standalone curve-based and purely data-driven models, the proposed hybrid model demonstrates superior physical consistency and reduced performance degradation under extrapolated conditions.
The developed hybrid model was further embedded within a model predictive control (MPC) framework to evaluate advanced control strategies. The MPC implementation effectively regulates control inputs to reduce power consumption while maintaining thermal comfort. Pareto-front analyses reveal the trade-offs between energy savings and comfort objectives across cooling and heating seasons.
Overall, this research establishes an end-to-end digital-twin framework for VRF systems that integrates field experimentation, data-driven modeling, hybrid physics-informed modeling, and optimized control. The proposed framework advances the accuracy, robustness, and practical deployability of VRF modeling for real-time control and smart building applications.
Future work will enhance data representativeness for underutilized indoor units (IDUs) through targeted experiments to improve model generalization in rarely observed operating regions. The scalability of the proposed framework will be evaluated across VRF systems with different configurations. Multi-domain co-simulation integrating building thermal and distribution-network models will be explored to assess demand-side flexibility and grid-interactive performance. Finally, field implementation of the proposed MPC strategy will be conducted to validate energy savings, comfort impact, robustness, and operational reliability under practical conditions.
Doctoral Dissertation
Finite Volume Modeling of Dehumidification and Frosting Phenomena in Compact Heat Exchangers With Generalized Flows
by Suraj Krishnamurti
With increasing global demand for heat pumps, increasing their efficiency is an extremely important step to meet the net zero carbon emissions target and combat climate change. Heat exchangers (HXs) are critical components of heat pumps, and increasing their effectiveness can significantly improve the system's efficiency. Improving the effectiveness of heat exchangers also affects many other industrial processes, including those in the chemical, dairy, and power sectors.
In recent years, there has been a lot of research on the modeling and simulation of heat exchangers, as this reduces prototyping and experimental costs for engineers. Over the years, the finite volume modeling approach has gained the most traction, which provides extremely high prediction accuracy while keeping computational costs low. These models can then be leveraged to perform system simulations and design optimization, thereby saving design time and improving productivity.
However, as the HX market grows and its applications expand, the need for more sophisticated models that can account for the various phenomena that impact their performance increases. In particular, there is a growing interest in moisture condensation and frost formation in HXs. Internal moisture condensation is extremely important for designing flue gas HXs, where we need to maximize latent heat recovery to maximize the efficiency of the heating furnace, which in turn requires accurate prediction of sensible and latent heat loads. Frost formation is important for the outdoor units of HXs in cold-climate heat pumps. Both of them involve modeling simultaneous heat and mass transfer, which is a challenging problem. Another point of interest in HX modeling are HXs with non-conventional circuitry and flow paths. Having fast and robust models enables efficient design of HXs, as it becomes very easy to conduct extensive parametric and optimization studies.
This research aims to build on prior work on heat exchanger modeling by developing advanced finite-volume models for different types of HXs under dehumidifying and frosting conditions. These models are designed to be faster and more robust than the state of the art, reducing engineering time. The novelty of this research is summarized as follows:
- Developed a first-of-its-kind finite control volume modeling approach that can handle multiple fluids flowing in any arbitrary direction. The proposed modeling approach provides an alternative solution to the multistream plate-type HX problem, avoiding the use of non-linear solvers and thereby reducing computational time and improving model robustness.
- Developed a stable and fast quasi-steady frost modeling approach for air-to-refrigerant heat exchangers. This model overcomes the limitations of state-of-the-art transient models, enabling rapid and efficient design of HXs under frosting conditions.
- Developed a finite volume modeling approach for moist gas flows inside tubes, which are extremely important for designing HXs for maximizing latent heat recovery from flue gases. These HXs are primarily used to improve the efficiency of domestic gas furnaces.
Doctoral Dissertation
Performance Enhancement of Elastocaloric Cooling Through System Optimization, Novel Material Architectures, and Scalable Design
by Het Mevada
Shape memory alloy (SMA) based elastocaloric cooling has matured substantially over the past decade, advancing from proof-of-concept demonstrations to lab-scale prototypes, while offering large latent heat, high Carnot efficiency, and zero global warming potential. Bridging the remaining gap toward practical deployment, this dissertation presents integrated research spanning numerical modeling, experimental validation, and system-level analysis to advance heat transfer optimization, material architecture, and scalable system design.
In this study, heat transfer optimization is first addressed using the thermal utilization ratio (Z*), a novel non-dimensional parameter incorporating SMA thermophysical properties and interfacial heat transfer coefficient into a unified system metric. Using a validated dynamic model of a tubular NiTi system operating in active regeneration, an optimal Z* of 0.42 yields a maximum temperature lift of 27 K. Extended to alternative materials and geometries, slot and groove SMA configurations enhance temperature lift by 125% and 93% over the baseline, respectively, confirming Z* as a practical design guideline across diverse elastocaloric configurations.
Building on this framework, strain maldistribution is identified as a fundamental performance-limiting mechanism and addressed through two complementary experimental approaches. First, a multi-stage, staggered-tube system with sequentially varying austenite finish temperatures (Af), fabricated through a heat treatment process, achieves a temperature lift of 38 K and a cooling power of 75 W, a 45% improvement over the single-Af baseline. Secondly, a gradient-Af NiTi regenerator with continuous transformation-temperature variation along the tube length yields a temperature lift of 16.5 K and cooling power of 44 W, also representing a 40% performance improvement. Together, these architectures achieve a minimum 66% reduction in strain maldistribution and extend the operational temperature range from 15–35°C to 0–70°C, accompanied by design guidelines for Af optimization across varying system scales and applications.
Recognizing that tubular geometries impose fundamental constraints on heat transfer surface area and manufacturability, a stacked SMA sheet-based system is developed, leveraging the high specific surface area of sheet-form with stamping-based fabrication, eliminating costly wire-EDM methods. A modular design enables independent assembly and scaling of regenerator modules. A Single module system was optimized in two phases considering operational and design parameters using a surrogate model. Optimization across single-, multi-, and hybrid configurations achieves 1 kW cooling power and a 10 K temperature lift. Contextualizing these advances, a comparative assessment of solid-state technologies further positions elastocaloric cooling in terms of performance, scalability, and commercialization readiness.
Collectively, the frameworks, experimental validations, and system architectures presented advance the technology readiness of elastocaloric cooling, establishing a concrete pathway toward commercially viable, environmentally sustainable cooling systems to meet the growing global demand.
Doctoral Dissertation
Modeling and Performance Evaluation of Cold Climate Heat Pump Systems in Commercial and Residential Buildings
by Dhahyun Kang
Heat pumps are increasingly recognized as a critical technology for building decarbonization due to their ability to provide space heating and cooling with efficiencies well above those of conventional fossil-fuel systems. However, their adoption for electrified heating in cold climates remains limited in both residential and commercial applications, owing to capacity degradation and efficiency losses at low ambient temperatures. While substantial research exists on the component-level performance of cold climate heat pumps (CCHPs), there is a lack of building-level analysis evaluating their operation under real-world cold climate conditions. Additionally, few studies have incorporated the performance of low-GWP (Global Warming Potential) refrigerant alternatives directly into whole-building energy models or examined the feasibility of integrated cascaded heat pump systems for simultaneous space heating and domestic hot water production. This thesis addresses these gaps through two complementary studies.
The first evaluates the quasi-steady-state heating performance of a commercially available air-source rooftop heat pump in a modeled outpatient healthcare facility located in ASHRAE Climate Zone 5B, using EnergyPlus™ as the simulation engine. R-410A serves as the baseline refrigerant, with R-454B, R-32, R-290, and R-1234yf assessed as low-GWP alternatives using literature-based performance correction factors applied under consistent system boundary conditions. R-32 emerges as the most promising alternative, offering improved SCOP over R- 410A with comparable capacity and near-term market feasibility as an A2L refrigerant. Although R-290 achieved the highest SCOP and greatest cost savings, its capacity loss at low ambient temperatures and charge limitation constraints reduce its suitability for large-scale commercial adoption. R-454B performed comparably to R-410A with minimal efficiency penalty, making it a viable near-term drop-in replacement. R-1234yf showed higher winter electricity consumption but exhibited greater efficiency during warmer months, suggesting it is better suited to mild- climate applications. A Life Cycle Climate Performance (LCCP) analysis confirmed that indirect emissions from energy use dominate total climate impact, making system efficiency a more critical factor than refrigerant GWP alone.
The second study develops and validates a field-calibrated BEopt / EnergyPlus™ model for a 382.4 m 2 (4,116 ft² ) single-family residence in Ellicott City, MD (ASHRAE Climate Zone 4A), and uses it to evaluate the energy, economic, and environmental performance of a gas-to- electric retrofit. The retrofit replaces a natural gas furnace and gas-powered water heater with a cascaded R-32 variable refrigerant flow ( VRF) system and R-134a heat pump water heater (HPWH). The model was validated against field measurements collected during the 2024–2025 heating season, with simulation errors within the ±15% tolerance specified by ASHRAE Guideline 14. Field data were used to calculate the COP of the cascaded system across three water heater setpoint temperatures, with the system COP ranging from 3.13 at 55°C to 2.22 at 65°C, confirming that setpoint temperature is a meaningful driver of water heating efficiency. Utility bill analysis showed source energy savings of up to 50% in the peak winter months, though overall utility costs increased due to the higher per-unit electricity costs in the Maryland market. Performance projections across five U.S. climate regions showed annual source energy savings of 11.1% to 37.0% and CO2 emissions reductions of 26% to 64%, with the strongest results in colder climates. Life-cycle cost analysis over a 30-year horizon indicates that the retrofit carries a modest cost premium, the smallest in high-HDD climates where energy savings are greatest.
Together, these results demonstrate that both low-GWP refrigerant substitution and cascaded heat pump retrofits represent technically viable, energy-efficient pathways toward building decarbonization, and highlight the importance of building-level analysis over component-level evaluation alone.
Master's Thesis
A Silicon and Silicon Carbide Bonding Methodology for Cooling High Heat Flux Electronics
by Kyle Martin
This thesis involves the development of a novel bonding procedure for Silicon and Silicon Carbide substrates used in microfluidic cooling devices for high-heat-flux electronics. As power densities in computer chips increase, cooling devices with small, complex structures need to be developed. Silicon and Silicon Carbide are two of the most popular material choices for these devices. Many cooling devices made from these materials require effective bonding between their components to prevent leakage of the process fluids used. While extremely important, leak-proof bonding at elevated pressures has proven difficult to achieve. To address this challenge, a novel bonding procedure for a Silicon manifold-microchannel heat sink was developed.
Since the components of the manifold-microchannel heat sink were made from Silicon wafers with microscale etched geometries, solder-assisted wafer bonding was chosen as the bonding method. A unique multi-layer solder comprising three different metals was developed as the bonding material. After depositing the material onto the manifold and microchannels, a novel process using a Rapid Thermal Annealer (RTA) was developed to bond the components.
After the manifold and microchannel components were bonded to form the complete cooling device, pressure testing was performed to assess the bond strength. These tests revealed that the device was leak-proof up to 60 psi and could likely support pressures up to higher pressures if needed. While the pressure-tested device used microchannels and manifolds, both made of Silicon, recent tests indicate that the developed bonding procedure is also effective for both Si-to-SiC and SiC-to-SiC substrates.
Master's Thesis
Development and Optimization of Low-GWP Heat Pump Systems for Industrial Wood Drying
by Tamoy Seabourne
Wood drying is a quality-critical and energy-intensive process in lumber manufacturing, and it remains an important target for industrial electrification and decarbonization. Dehumidification kilns using vapor-compression heat pumps can remove moisture by condensing water at an evaporator and reheating the dried air at a condenser. Still, kiln schedules impose a wide operating envelope that challenges conventional low-temperature heat pump designs, especially under large temperature lift and evolving latent loads. This thesis develops a schedule-aware, component-based modelling framework for heat-pump-driven wood drying and couples it with steady-state experimental evaluation to quantify performance, operating constraints, and improvement pathways. A system-level quasi–steady-state model is constructed to link kiln schedule targets to psychrometric states, coil duties, electrical input, and the specific moisture extraction rate (SMER), using air-side bypass and airflow assumptions consistent with industrial operation and a 10-coefficient heat pump performance representation for computationally efficient cycle simulation. The model is validated against industrial drying data, showing good agreement in moisture content evolution and capturing characteristic declines in drying rate, dryer effectiveness, and SMER over time. An experimental campaign using a closed-loop facility with a virtual load establishes baseline performance of a commercial dehumidification unit (R-134a). It evaluates targeted upgrades, including low-GWP refrigerant substitution, resized heat exchangers, an expansion valve, and high-temperature-capable air handling. A direct comparison at 40 °C and 50% RH shows an increased heating capacity of 6.3 kW and an improved SMER of 1.8, with a comparable COP to the baseline that has a heating capacity of 5 kW and a SMER of 1.65. The upgraded configuration demonstrates stable operation over a broader operating range, including conditions above the conventional low-temperature envelope and up to conditions of 63 oC and 28% RH, demonstrating a SMER of 1.5 with a capacity of 7.1 kW.
Finally, steady-state test results are integrated into the schedule-driven simulation framework to assess full-drying implications, indicating that the upgraded system can maintain schedule-consistent moisture trajectories while reducing total power by reducing auxiliary heating demand and increasing SMER during key portions of the drying process. Overall, this thesis provides an experimentally anchored modelling workflow for evaluating and improving heat pump wood drying systems under realistic schedule variation and highlights design levers such as evaporator approach temperature, pressure drop, airflow/bypass control, and cycle architecture that govern energy use and moisture removal efficiency.
Master's Thesis
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