An effective preconditioning strategy for volume penalized incompressible/low Mach multiphase flow solvers
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This work applies a new combination of techniques for the fully resolved simulation of compressible, gas–particle multiphase flows. Here, the adaptive wavelet collocation method is used to dynamically, and efficiently, adapt the computational grid to localized flow features and the particles. A characteristic-based volume penalization method that imposes arbitrary Dirichlet, Neumann, or Robin-type immersed boundary conditions, is used to enforce the no-slip condition at particle surfaces. A hard-sphere collision model is applied to capture the particle–particle collisions. Proof of concept test cases are presented, showcasing the dynamic grid adaptation and fully resolved two-way coupling between the phases that is possible with this approach. Results for a shock-driven single cylinder under viscous and inviscid conditions are presented along with a demonstration of a shock interacting with a cloud of randomly distributed cylinders and spheres.
Advancements to the adaptive wavelet-collocation method over the last decade have opened up a number of new possible areas for active research. Volume penalization techniques allow complex immersed boundary conditions to be used with high efficiency for both internal and external flows. Anisotropic methods make it possible to use body-fitted meshes while still taking advantage of the dynamic adaptability properties wavelet-based methods provide. The parallelization of the approach has made it possible to perform large high-resolution simulations of detonation initiation and fluid instabilities to uncover new physical insights that would otherwise be difficult to discover. Other developments include space-time adaptive methods and nonreflecting boundary conditions. This article summarizes the work performed using the adaptive wavelet-collocation method developed by Vasilyev and coworkers over the past decade.
The baseline space shuttle galley was designed to utilize lightweight rehydratable foods, to be prepared for consumption by rehydration with chilled or hot water. The impact is examined of an extension of food types to include thermostabilized food, at ambient temperature, and frozen foods on the baseline design of the shuttle galley. Weight, volume, and power penalities associated with heating thermostabilized and frozen foods by means of a hot air convection heating system and a conduction heating system are determined along with the impact on crew/galley interface and meal preparation.
Ion exchange offers a pathway to impose residual compressive stresses to mitigate the electro-chemo-mechanical cracking of solid-state electrolytes such as lithium lanthanum zirconium oxide. This study uses a coupled multiscale framework (integrating density functional theory (DFT), molecular dynamics (MD), and continuum modeling) to examine how exchange ion size influences stress, diffusion, fracture toughness, and electronic properties. Larger isovalent ions (Na + , Ag + , K + ) were exchanged with Li + , with DFT confirming their preference for octahedral 96h sites and a linear relationship between ion size and chemical free expansion coefficient. MD simulations reveal stress and concentration effects on exchange ion diffusivity at elevated temperatures, with Na + and Ag + maintaining favorable mobility while K + showing concentration-dependent clustering. Continuum modeling predicts the range of fracture strength improvements and the required ion exchange concentration profile. It was shown that a 5% surface exchange concentration can induce ∼0.6 GPa of surface compressive stress using Na + and ∼1.0 GPa of surface compressive stress using Ag + . On the other hand, larger ion exchange species may penalize Li + diffusivity by increasing the activation volume and activation energy. Interestingly, Na + has a negligible penalty on Li-ion diffusivity. The room temperature Li + ion diffusivity is reduced by ∼40% with Ag + ion exchange. Electronic band structure analysis shows no size-dependent change in the bandgap, though Ag + introduces localized defect states near the valence band maximum. This study highlights ion size as a key factor in optimizing LLZO properties, offering a framework to improve the solid-state battery performance.
Abstract Heat pumping through thermoelectric devices has many advantages over traditional cooling. However, their current efficiency is a limiting factor in their implementation. In this paper, we approach the non-convex topology optimization of thermoelectrical elements for cooling applications through the method of moving asymptotes (MMA) to improve their cooling capabilities per watt usage. The optimization problem is defined for a given power budget, aiming for the minimum temperature with a known heat pumping need. The introduction of power as a constraint justifies the introduction of the voltage gradient across the thermocouple as a design variable to maintain the thermoelectrical device in its optimum power-to-heat extraction ratio. To better understand the convergence of this non-convex problem, we present a two-variable analytical thermoelectric optimization model. This example provides information on how to select the penalty parameters used to scale the three material coefficients involved in the problem to obtain lower objective values and better convergence using MMA. The analytical model shows the non-convexity of the problem and provides the recommendation to use penalization coefficients of the form $$p_k=p_{\sigma }>p_{\alpha }=1$$ p k = p σ > p α = 1 for the thermal conductivity, electrical conductivity, and Seebeck coefficients. We tested these penalization coefficients through optimizations of a model based on the 1MC10-031 commercial thermoelectric-cooler (TEC) using the finite element method (FEM). These penalization coefficients provided local minima without the need for volume constraints. With this procedure, we found designs that provided temperatures close to 10 degrees lower using 60% less semiconductor material volume compared to the initial design.
We design heat exchangers using two topology optimization approaches: the density, i.e. volume fraction and level set methods. Our goal is to maximize the heat exchange between two fluids in separate channels while constraining the pressure drop across each channel. The heat exchanger is modeled with a coupled thermal-flow formulation. The flow is governed by an isothermal and incompressible Stokes-Brinkman equation and the heat transfer is governed by a convection-diffusion equation with high Peclet number. We solve one set of Stokes-Brinkman equations per fluid. Each Brinkman term in the flow equation serves to model the other phase as a solid, thereby preventing mixing. We first represent the solid and fluid phases using a volume fraction variable and apply a SIMP-like penalization in the Brinkman term to drive the optimization to a discrete design. The cost and constraint function derivatives are automatically calculated with the library pyadjoint and the optimization is performed by the Method of Moving Asymptotes. In a second optimization formulation, we use the level set approach to define the interface that separates the two fluids. Pyadjoint calculates the shape derivatives of the cost and constraint functions and the Hamilton-Jacobi advects the interface, allowing for topological changes. We present results in two dimensions and discuss the advantages and disadvantages of each approach.
The motivation behind Integrated Demand Management (IDM) research is to explore possible improvements to United States National Airspace System (NAS) performance that could be realized through procedural integration of strategic traffic flow management capabilities, such as the Collaborative Trajectory Options Program (CTOP), and tactical capabilities, such as Time Based Flow Management (TBFM). An initial IDM concept for clear weather operations was developed and evaluated for potential benefits, including efficiency, delay reduction, predictability and throughput, and to identify any major issues that might represent a showstopper for a fielded application. Newark Liberty International Airport (EWR) arrival operations provided a use case for concept development. EWR uses miles-in-trail (MIT) metering to regulate demand into TBFM during high volume operations, and short-haul flights are often penalized with excessive, last-minute ground delays when the overhead stream is saturated. IDM addresses this problem by replacing MIT conditioning with CTOP to better manage the demand delivery to the TBFM entry points. A quasi-real time high-fidelity simulation that would normally involve participants was conducted using heuristic-based procedures that mimicked operators behaviors instead. Five total conditions were compared: two baseline conditions with MIT delivery to TBFM entry points using two different TBFM settings; and three IDM conditions: one with airborne speed control using an Required Time of Arrival (RTA) capability, a second without RTA, and a third with no wind forecast errors. Results suggest that the IDM concept can deliver traffic more efficiently by shifting the delays from airborne to ground for both RTA and non-RTA conditions, while maintaining a target throughput rate. The results also suggest that with good predictability of airport capacity, excessive TBFM ground delay can be minimized by applying more strategic CTOP delay, increasing predictability for the airline operators. Overall, the results indicate that the implementation of an IDM concept under clear weather conditions can improve NAS system performance. Future IDM research aims to expand the concept to address demandcapacity imbalance d severe weather.
Electric propulsion offers dramatic new vehicle mission capabilities, not possible with turbine or reciprocating engines; including high reliability and efficiency, low engine weight and maintenance, low cooling drag and volume required, very low noise and vibration, and zero emissions. The only penalizing characteristic of electric propulsion is the current energy storage technology level, which is set to triple over the next 5-10 years through huge new investments in this field. Most importantly, electric propulsion offers incredible new degrees of freedom in aircraft system integration to achieve unprecedented levels of aerodynamic, propulsive, control, and structural synergistic coupling. A unique characteristic of electric propulsion is that the technology is nearly scale-free, permitting small motors to be parallelized for fail-safe redundancy, or distributed across the airframe for tightly coupled interdisciplinary functionality without significant impacts in motor-controller efficiency or specific weight. Maximizing the potential benefit of electric propulsion is dependent on applying this technology to synergistic mission concepts. The vehicle missions with the most benefit include those which constrain environmental impact (or limit noise, exhaust, or emission signatures) are short range, or where large differences exist in the propulsion system sizing between takeoff and cruise conditions. Electric propulsion offers the following unique capabilities that other propulsion systems can t provide for short range Vertical Takeoff and Landing (VTOL) aircraft; elimination of engine noise and emissions, drastic reduction in engine cooling and radiated heat, drastic reduction in vehicle vibration levels, drastic improvement in reliability and operating costs, variable speed output at full power, for improved cruise efficiency at low tip-speed, elimination of high/hot sizing penalty, and reduction of engine-out penalties.
Communications subsystem tradeoffs were undertaken to establish a low cost and low weight design consistent with the mission requirements. Because of the weight constraint of the Thor/Delta launched configuration, minimum weight was emphasized in determining the Thor/Delta design. In contrast, because of the greatly relaxed weight constraint of the Atlas/Centaur launched configuration, minimum cost and off the shelf hardware were emphasized and the attendant weight penalities accepted. Communication subsystem hardware elements identified for study included probe and bus antennas (CM-6, CM-17), power amplifiers (CM-10), and the large probe transponder and small probe stable oscillator required for doppler tracking (CM-11, CM-16). In addition, particular hardware problems associated with the probe high temperature and high-g environment were investigated (CM-7).
As artificial intelligence (AI) becomes widespread, there is increasing attention on investigating bias in machine learning (ML) models. Previous research concentrated on classification problems, with little emphasis on regression models. This paper presents an easy-to-apply and effective methodology for mitigating bias in bagging and boosting regression models, that is also applicable to any model trained through minimizing a differentiable loss function. Our methodology measures bias rigorously and extends the ML model's loss function with a regularization term to penalize high correlations between model errors and protected attributes. We applied our approach to three popular tree-based ensemble models: a random forest model (RF), a gradient-boosted model (GBT), and an extreme gradient boosting model (XGBoost). We implemented our methodology on a case study for predicting road-level traffic volume, where RF, GBT, and XGBoost models were shown to have high accuracy. Despite high accuracy, the ML models were shown to perform poorly on roads in minority-populated areas. Our bias mitigation approach reduced minority-related bias by over 50%.
With increasing freshwater scarcity, advanced process design mechanisms such as Closed-Circuit Reverse Osmosis (CCRO) and Digital/Physical Twin systems are gaining traction in water treatment and reuse operations. While digital and physical twin models enable improved system insight and control, their development is often expensive and computationally intensive, requiring large volumes of synthetic or experimental data to characterize underlying process dynamics. This work introduces a sparse surrogate modeling framework to estimate power consumption from measured flow and pressure variables, along with their nonlinear polynomial and interaction expansions. To ensure model reliability and reduce overfitting, a two-stage pipeline is proposed. First, a dynamic data filtering algorithm is employed to remove uninformative observations and transient operational states. Second, a sparse penalized regression technique is applied to select a minimal set of parsimonious features. The proposed model achieves high sparsity, retaining only 7 out of 34 candidate features (≈79.41% sparsity) while delivering a root mean square error (RMSE) of 0.072 on the test dataset.
Key aspects of the design of sealing systems for On Rotor Combustion/Wave Rotor (ORC/WR) systems were addressed. ORC/WR systems generally fit within a broad class of pressure gain Constant Volume Combustors (CVCs) or Pulse Detonation Combustors (PDCs) which are currently being considered for use in many classes of turbine engines for dramatic efficiency improvement. Technology readiness level of this ORC/WR approaches are presently at 2.0. The results of detailed modeling of an ORC/WR system as applied to a regional jet engine application were shown to capture a high degree of pressure gain capabilities. The results of engine cycle analysis indicated the level of specific fuel consumption (SFC) benefits to be 17 percent. The potential losses in pressure gain due to leakage were found to be closely coupled to the wave processes at the rotor endpoints of the ORC/WR system. Extensive investigation into the sealing approaches is reported. Sensitivity studies show that SFC gains of 10 percent remain available even when pressure gain levels are highly penalized. This indicates ORC/WR systems to have a high degree of tolerance to rotor leakage effects but also emphasizes their importance. An engine demonstration of an ORC/WR system is seen as key to progressing the TRL of this technology. An industrial engine was judged to be a highly advantageous platform for demonstration of a first generation ORC/WR system. Prior to such a demonstration, the existing NASA pressure exchanger wave rotor rig was identified as an opportunity to apply both expanded analytical modeling capabilities developed within this program and to identify and fix identified leakage issues existing within this rig. Extensive leakage analysis of the rig was performed and a detailed design of additional sealing strategies for this rig was generated.