PC Krause & Associates (United States)

This paper presents a novel framework for the automated enumeration and dynamic optimization of thermofluid system architectures, demonstrated on air cycle machine (ACM) thermal management systems. The approach addresses the challenge of exploring large design spaces by combining graph-based modeling, symbolic equation generation, and dynamic optimization to automatically derive and evaluate the governing equations for each feasible architecture. A case study optimizes 164 ACM architectures over a 4,000-second mission profile, targeting two objectives: total entropy generation and time-averaged bleed air mass flow rate (<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</i><sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> norm). Results show that optimal architectures differ across metrics, revealing architecture-level trade-offs. The top-performing designs align with known practical systems. The methodology is general and scalable, with potential extensions to two-phase thermal loops, vapor compression systems, and other regenerative energy systems.

In this research, a method-of-moments-based model has been established and structured to enable rapid evaluation of the electromagnetic performance of V-shaped interior permanent magnet machines. Contributions to the model formulation include the use of a judicious combination of linear and nonlinear elements to evaluate machine behavior under magnetic saturation of stator and rotor steels. Also included is a straightforward means to include multiple operating points with minimal additional computational expense. The proposed approach has been validated using commercial finite-element-based software. Subsequently, it has been applied in the design optimization of a vehicular propulsion drive, where six operating points are specified. It is shown that the resulting model enables a rigorous search of the design space that includes material selection, machine geometry, winding layout, and stator excitation at each operating point.

View Video Presentation: https://doi.org/10.2514/6.2023-4544.vid The increased use of simulation models in aerospace system design necessitates broad model validation. To aid in validating models of electric generators, a solid-state-relay-based device is designed for augmenting the step-load testing capabilities of load banks. The device is a three-phase ac switch utilizing common-emitter IGBT modules to perform commutation in lieu of the electromagnetic relays in load banks. Step-load testing is performed on a 125 kW automotive electric machine operating as a generator both with and without the device in order to evaluate the step-load transition characteristics in each case. The results from testing without the device show a transition characteristic heavily influenced by the non-ideal behavior of load bank relays up to 31 ms after transient inception, rendering the analysis of generator response in that often-important region impractical. With the assistance of the solid-state relay device, non-ideal transition characteristics are largely limited to the first 5 μs for load application steps and the first 55 μs for load rejection steps for this test setup.

Data-driven decision-making in power and thermal technology investment for advanced platforms is supported by the development of the High-Level Integration sizing Tool for Electrical architectures (HighLITE). In response to the continued analysis of advanced platforms and to provide insight into electrical technology impacts on the entire system, HighLITE was developed to enable rapid electrical power system (EPS) architecture size, weight, and power (SWaP) calculations using relevant databases and design tools. The tool provides SWaP guidance with applicable designs and parameters. The goal is to enable fast single-point design, provide insights into the trade space, understand uncertainties, and automate the conceptual level analysis process. The SWaP design points are generated based on a user-defined architecture, input parameters, and objectives by leveraging databases and sizing functions.

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Bacterial growth is remarkably robust to environmental fluctuations, yet the mechanisms of growth-rate homeostasis are poorly understood. Here, we combine theory and experiment to infer mechanisms by which Escherichia coli adapts its growth rate in response to changes in osmolarity, a fundamental physicochemical property of the environment. The central tenet of our theoretical model is that cell-envelope expansion is only sensitive to local information such as enzyme concentrations, cell-envelope curvature, and mechanical strain in the envelope. We constrained this model with quantitative measurements of the dynamics of E. coli elongation rate and cell width after hyperosmotic shock. Our analysis demonstrated that adaptive cell-envelope softening is a key process underlying growth-rate homeostasis. Furthermore, our model correctly predicted that softening does not occur above a critical hyperosmotic shock magnitude and precisely recapitulated the elongation-rate dynamics in response to shocks with magnitude larger than this threshold. Finally, we found that to coordinately achieve growth-rate and cell-width homeostasis, cells employ direct feedback between cell-envelope curvature and envelope expansion. In sum, our analysis points to new cellular mechanisms of bacterial growth-rate homeostasis and provides a practical theoretical framework for understanding this process.Significance StatementThe bacterial cell envelope is the critical structure that defines cell size and shape, and its expansion therefore defines cell growth. Although size, shape, and growth rate are important cellular variables that are robust to environmental fluctuations, the feedback mechanisms by which these variables influence cell-envelope expansion are unknown. Here, we explore how E. coli cells achieve growth-rate and cell-width homeostasis during fluctuations in osmolarity, a key environmental property. A biophysical model in which the cell envelope softens after an osmotic shock and envelope expansion depends directly on local curvature quantitatively recapitulated all experimental observations. Our study elucidates new mechanisms of bacterial cell morphogenesis and highlights the deep interplay between global cellular variables and the mechanisms of cell-envelope expansion.

Dancing has been recommended as a suitable home-based physical activity during the quarantine period associated with the COVID-19 pandemic. Dancing can reduce sedentary behavior and thereby maintain physical and emotional health. The aim of this article was to provide support to dance, fitness, and/or other health professionals in guiding individuals wishing to practice dancing activities at home. By considering dancing as a strategy to increase levels of physical activity at home, this article is divided into three sections: i) the structure of a dance session, ii) elements of aerobic fitness, and iii) safety considerations. A home setting dance session lasts ~40-50 minutes, including the warm-up, the specific dancing activities, and the cool-down.

View Video Presentation: https://doi.org/10.2514/6.2021-1421.vid Specialized functionalities in an aircraft power system often require dedicated hardware that are only operated during distinct mission segments and are otherwise inactive. Active load management can utilize these loads during dormancy to improve power quality with zero to minimal volume and weight cost to the aircraft. The feasibility of applying active load management to improve power quality was explored in this paper for a typical aircraft electrical power system (EPS). Electrical power quality improvement was achieved through minimal redesign and the lessons learnt have been used to develop a general guideline for other power systems.

Grid-connected photovoltaic (PV) energy systems present a variable power source. They are often treated as “negative load,” especially for small systems, and require grid reserve margins and management resources to address their stochastic operation. However, inverters linked to PV energy systems probably represent the fastest resource on the grid, able to adjust operation on a cycle-by-cycle basis. This work reviews and quantifies PV variability, with emphasis on fast time scales. Operating needs if batteries are used to manage variability are presented. A reference case establishes the rates of change and storage needs in megawatt-scale installations. Alternative power electronics operating strategies are explored to mitigate variability directly at the source. Variability measures based on a time-window standard deviation lead to fast adaptive strategies. Controls that trade off energy production against variability are presented. Measured data are used to determine and compare performance expectations among several different control methods. Results, validated with scaled experiments, show that fast variability can decrease by about an order of magnitude given the right control strategy, implying battery capacity reduction of about <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$5\times $ </tex-math></inline-formula> compared to systems in which batteries manage variation. System-level economics strongly favor large variability reduction linked to modest energy reduction.