A two-stage design framework for optimal spatial packaging of interconnected fluid-thermal systems

Optimal spatial packaging of interconnected subsystems and components with coupled physical (thermal, hydraulic, or electromagnetic) interactions, or SPI2, plays a vital role in the functionality, operation, energy usage, and life cycle of practically all engineered systems, from chips to ships to aircraft. However, the highly nonlinear spatial packaging problem, governed by coupled physical phenomena transferring energy through highly complex and diverse geometric interconnects, has largely resisted automation and quickly exceeds human cognitive abilities at moderate complexity levels. The current state-of-the-art in defining an arrangement of these functionally heterogeneous artifacts still largely relies on human intuition and manual spatial placement, limiting system sophistication and extending design timelines. Spatial packaging involves packing and routing, which are separately challenging NP-hard problems. Therefore, solving the coupled packing and routing (PR) problem simultaneously will require disruptive methods to better address pressing related challenges, such as system volume reduction, interconnect length reduction, ensuring non-intersection, and physics considerations. This dissertation presents a novel automated two-stage sequential design framework to perform simultaneous physics-based packing and routing (PR) optimization of fluid-thermal systems. In Stage 1, unique spatially-feasible topologies (i.e., how interconnects and components pass around each other) are enumerated for given fluid-thermal system architecture. It is important to guarantee a feasible initial graph as lumped-parameter physics analyses may fail if components and/or routing paths intersect. Stage 2 begins with a spatially-feasible layout, and optimizes physics-based system performance with respect to component locations, interconnect paths, and other continuous component or system variables (such as sizing or control). A bar-based design representation enables the use of a differentiable geometric projection method (GPM), where gradient-based optimization is used with finite element analysis. In addition to geometric considerations, this method supports optimization based on system behavior by including physics-based (temperature, fluid pressure, head loss, etc.) objectives and constraints. In other words, stage 1 of the framework supports systematic navigation through discrete topology options utilized as initial designs that are then individually optimized in stage 2 using a continuous gradient-based topology optimization method. Thus, both the discrete and continuous design decisions are made sequentially in this framework. The design framework is successfully demonstrated using different 2D case studies such as a hybrid unmanned aerial vehicle (UAV) system, automotive fuel cell (AFC) packaging system, and other complex multi-loop systems. The 3D problem is significantly more challenging than the 2D problem due to vastly more expansive design space and potential features. A review of state-of-the-art methods, challenges, existing gaps, and opportunities are presented for the optimal design of the 3D PR problem. Stage 1 of the framework has been investigated thoroughly for 3D systems in this dissertation. An efficient design framework to represent and enumerate 3D system spatial topologies for a given system architecture is demonstrated using braid and spatial graph theories. After enumeration, the unique spatial topologies are identified by calculating the Yamada polynomials of all the generated spatial graphs. Spatial topologies that have the same Yamada polynomial are categorized together into equivalent classes. Finally, CAD-based 3D system models are generated from these unique topology classes. These 3D models can be utilized in stage 2 as initial designs for 3D multi-physics PR optimization. Current limitations and significantly impactful future directions for this work are outlined. In summary, this novel design automation framework integrates several elements together as a foundation toward a more comprehensive solution of 3D real-world packing and routing problems with both geometric and physics considerations

Integrated design optimization methods for optimal sensor placement and cooling system architecture design for electro-thermal systems

Dynamic thermal management plays a very important role in the design and development of electro-thermal systems as these become more active and complex in terms of their functionalities. In highly power dense electronic systems, the heat is concentrated over small spatial domains. Thermal energy dissipation in any electrified system increases the temperature and might cause component failure, degradation of heat sensitive materials, thermal burnouts and failure of active devices. So thermal management needs to be done both accurately (by thermal monitoring using sensors) and efficiently (by applying fluid-based cooling techniques). In this work, two important aspects of dynamic thermal management of a highly dense power electronic system have been investigated. The first aspect is the problem of optimal temperature sensor placement for accurate thermal monitoring aimed toward achieving thermally-aware electrified systems. Strategic placement of temperature sensors can improve the accuracy of real-time temperature distribution estimates. Enhanced temperature estimation supports increased power throughput and density because Power Electronic Systems (PESs) can be operated in a less conservative manner while still preventing thermal failure. This work presents new methods for temperature sensor placement for 2- and 3-dimensional PESs that 1) improve computational efficiency (by orders of magnitude in at least one case), 2) support use of more accurate evaluation metrics, and 3) are scalable to high-dimension sensor placement problems. These new methods are tested via sensor placement studies based on a 2-kW, 60Hz, single-phase, Flying Capacitor Multi-Level (FCML) prototype inverter. Information-based metrics are derived from a reduced-order Resistance-Capacitance (RC) lumped parameter thermal model. Other more general metrics and system models are possible through application of a new continuous relaxation strategy introduced here for placement representation. A new linear Programming (LP) formulation is presented that is compatible with a particular type of information-based metric. This LP strategy is demonstrated to support the efficient solution of finely-discretized large-scale placement problems. The optimal sensor locations obtained from these methods were tested via physical experiments. The new methods and results presented here may aid the development of thermally-aware PESs with significantly enhanced capabilities. The second aspect is to design optimal fluid-based thermal management architectures through enumerative methods that help operate the system efficiently within its operating temperature limits using the minimum feasible coolant flow level. Expert intuition based on physics knowledge and vast experience may not be adequate to identify optimal thermal management designs as systems increase in size and complexity. This work also presents a design framework supporting comprehensive exploration of a class of single-phase fluid-based cooling architectures. The candidate cooling system architectures are represented using labeled rooted tree graphs. Dynamic models are automatically generated from these trees using a graph-based thermal modeling framework. Optimal performance is determined by solving an appropriate fluid flow distribution problem, handling temperature constraints in the presence of exogenous heat loads. Rigorous case studies are performed in simulation, with components having variable sets of heat loads and temperature constraints. Results include optimization of thermal endurance for an enumerated set of 4,051 architectures. In addition, cooling system architectures capable of steady-state operation under a given loading are identified. Optimization of the cooling system design has been done subject to a representative mission, consisting of multiple time-varying loads. Work presented in this thesis clearly shows that the transient effects of heat loads are expected to have important impacts on design decisions when compared to steady-state operating conditions

Integrated design optimization methods for optimal sensor placement and cooling system architecture design for electro-thermal systems

Dynamic thermal management plays a very important role in the design and development of electro-thermal systems as these become more active and complex in terms of their functionalities. In highly power dense electronic systems, the heat is concentrated over small spatial domains. Thermal energy dissipation in any electrified system increases the temperature and might cause component failure, degradation of heat sensitive materials, thermal burnouts and failure of active devices. So thermal management needs to be done both accurately (by thermal monitoring using sensors) and efficiently (by applying fluid-based cooling techniques). In this work, two important aspects of dynamic thermal management of a highly dense power electronic system have been investigated. The first aspect is the problem of optimal temperature sensor placement for accurate thermal monitoring aimed toward achieving thermally-aware electrified systems. Strategic placement of temperature sensors can improve the accuracy of real-time temperature distribution estimates. Enhanced temperature estimation supports increased power throughput and density because Power Electronic Systems (PESs) can be operated in a less conservative manner while still preventing thermal failure. This work presents new methods for temperature sensor placement for 2- and 3-dimensional PESs that 1) improve computational efficiency (by orders of magnitude in at least one case), 2) support use of more accurate evaluation metrics, and 3) are scalable to high-dimension sensor placement problems. These new methods are tested via sensor placement studies based on a 2-kW, 60Hz, single-phase, Flying Capacitor Multi-Level (FCML) prototype inverter. Information-based metrics are derived from a reduced-order Resistance-Capacitance (RC) lumped parameter thermal model. Other more general metrics and system models are possible through application of a new continuous relaxation strategy introduced here for placement representation. A new linear Programming (LP) formulation is presented that is compatible with a particular type of information-based metric. This LP strategy is demonstrated to support the efficient solution of finely-discretized large-scale placement problems. The optimal sensor locations obtained from these methods were tested via physical experiments. The new methods and results presented here may aid the development of thermally-aware PESs with significantly enhanced capabilities. The second aspect is to design optimal fluid-based thermal management architectures through enumerative methods that help operate the system efficiently within its operating temperature limits using the minimum feasible coolant flow level. Expert intuition based on physics knowledge and vast experience may not be adequate to identify optimal thermal management designs as systems increase in size and complexity. This work also presents a design framework supporting comprehensive exploration of a class of single-phase fluid-based cooling architectures. The candidate cooling system architectures are represented using labeled rooted tree graphs. Dynamic models are automatically generated from these trees using a graph-based thermal modeling framework. Optimal performance is determined by solving an appropriate fluid flow distribution problem, handling temperature constraints in the presence of exogenous heat loads. Rigorous case studies are performed in simulation, with components having variable sets of heat loads and temperature constraints. Results include optimization of thermal endurance for an enumerated set of 4,051 architectures. In addition, cooling system architectures capable of steady-state operation under a given loading are identified. Optimization of the cooling system design has been done subject to a representative mission, consisting of multiple time-varying loads. Work presented in this thesis clearly shows that the transient effects of heat loads are expected to have important impacts on design decisions when compared to steady-state operating conditions.U of I OnlyAuthor requested U of Illinois access only (OA after 2yrs) in Vireo ETD syste