Designing Complex Fluids
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Ewoldt, Randy H.↗
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nn-PINNs: Non-Newtonian physics-informed neural networks for complex fluid modeling
Time- and rate-dependent material functions in non-Newtonian fluids in response to different deformation fields pose a challenge in integrating different constitutive models into conventional computational fluid dynamic platforms. Considering their relevance in many industrial and natural settings alike, robust data-driven frameworks that enable accurate modeling of these complex fluids are of great interest. The main goal is to solve the coupled Partial Differential Equations (PDEs) consisting of the constitutive equations that relate the shear stress to the deformation and fully capture the behavior of the fluid under various flow protocols with different boundary conditions. Here, in this work, we present non-Newtonian physics-informed neural networks (nn-PINNs) for solving systems of coupled PDEs adopted for complex fluid flow modeling. The proposed nn-PINN method is employed to solve the constitutive models in conjunction with conservation of mass and momentum by benefiting from Automatic Differentiation (AD) in neural networks, hence avoiding the mesh generation step. nn-PINNs are tested for a number of different complex fluids with different constitutive models and for several flow protocols. These include a range of Generalized Newtonian Fluid (GNF) empirical constitutive models, as well as some phenomenological models with memory effects and thixotropic timescales. nn-PINNs are found to obtain the correct solution of complex fluids in spatiotemporal domains with good accuracy compared to the ground truth solution. We also present applications of nn-PINNs for complex fluid modeling problems with unknown boundary conditions on the surface, and show that our approach can successfully recover the velocity and stress fields across the domain, including the boundaries, given some sparse velocity measurements.
42 ENGINEERING↗
Conjugated Polyelectrolyte-Based Complex Fluids as Aqueous Exciton Transport Networks
The ability to assemble artificial systems that mimic aspects of natural light-harvesting functions is fascinating and attractive for materials design. Given the complexity of such a system, a simple design pathway is desirable. Here, we argue that associative phase separation of oppositely charged conjugated polyelectrolytes (CPEs) can provide such a path in an environmentally benign medium: water. We find that complexation between an exciton–donor and acceptor CPE leads to formation of a complex fluid. We interrogate exciton transfer from the donor to the acceptor CPE within the complex fluid and find that transfer is highly efficient. We also find that excess molecular ions can tune the modulus of the inter-CPE complex fluid. Even at high ion concentrations, CPEs remain complexed with significantly delocalized electronic wavefunctions. In conclusion, our work lays the rational foundation for complex, tunable aqueous light-harvesting systems via the intrinsic thermodynamics of associative phase separation.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Scientific machine learning for modeling and simulating complex fluids
The formulation of rheological constitutive equations—models that relate internal stresses and deformations in complex fluids—is a critical step in the engineering of systems involving soft materials. While data-driven models provide accessible alternatives to expensive first-principles models and less accurate empirical models in many engineering disciplines, the development of similar models for complex fluids has lagged. The diversity of techniques for characterizing non-Newtonian fluid dynamics creates a challenge for classical machine learning approaches, which require uniformly structured training data. Consequently, early machine-learning based constitutive equations have not been portable between different deformation protocols or mechanical observables. Here, we present a data-driven framework that resolves such issues, allowing rheologists to construct learnable models that incorporate essential physical information, while remaining agnostic to details regarding particular experimental protocols or flow kinematics. These scientific machine learning models incorporate a universal approximator within a materially objective tensorial constitutive framework. By construction, these models respect physical constraints, such as frame-invariance and tensor symmetry, required by continuum mechanics. We demonstrate that this framework facilitates the rapid discovery of accurate constitutive equations from limited data and that the learned models may be used to describe more kinematically complex flows. This inherent flexibility admits the application of these “digital fluid twins” to a range of material systems and engineering problems. We illustrate this flexibility by deploying a trained model within a multidimensional computational fluid dynamics simulation—a task that is not achievable using any previously developed data-driven rheological equation of state.
Science & Technology - Other Topics↗
Combustion, Complex Fluids, and Fluid Physics Experiments on the ISS
From the very first days of human spaceflight, NASA has been conducting experiments in space to understand the effect of weightlessness on physical and chemically reacting systems. NASA Glenn Research Center (GRC) in Cleveland, Ohio has been at the forefront of this research looking at both fundamental studies in microgravity as well as experiments targeted at reducing the risks to long duration human missions to the moon, Mars, and beyond. In the current International Space Station (ISS) era, we now have an orbiting laboratory that provides the highly desired condition of long-duration microgravity. This allows continuous and interactive research similar to Earth-based laboratories. Because of these capabilities, the ISS is an indispensible laboratory for low gravity research. NASA GRC has been actively involved in developing and operating facilities and experiments on the ISS since the beginning of a permanent human presence on November 2, 2000. As the lead Center both Combustion, Fluid Physics, and Acceleration Measurement GRC has led the successful implementation of an Acceleration Measurement systems, the Combustion Integrated Rack (CIR), the Fluids Integrated Rack (FIR) as well as the continued use of other facilities on the ISS. These facilities have supported combustion experiments in fundamental droplet combustion fire detection fire extinguishment soot phenomena flame liftoff and stability and material flammability. The fluids experiments have studied capillary flow magneto-rheological fluids colloidal systems extensional rheology pool and nucleate boiling phenomena. In this paper, we provide an overview of the experiments conducted on the ISS over the past 12 years. We also provide a look to the future development. Experiments presented in combustion include areas such as droplet combustion, gaseous diffusion flames, solid fuels, premixed flame studies, fire safety, and super critical oxidation processes. In fluid physics, experiments are discussed in multiphase flows, capillary phenomena, and heat pipes. Finally in complex fluids, experiments in rheology and soft condensed materials will be presented.
Motil, Brian↗
Combustion, Complex Fluids, and Fluid Physics Experiments on the ISS
From the very early days of human spaceflight, NASA has been conducting experiments in space to understand the effect of weightlessness on physical and chemically reacting systems. NASA Glenn Research Center (GRC) in Cleveland, Ohio has been at the forefront of this research looking at both fundamental studies in microgravity as well as experiments targeted at reducing the risks to long duration human missions to the moon, Mars, and beyond. In the current International Space Station (ISS) era, we now have an orbiting laboratory that provides the highly desired condition of long-duration microgravity. This allows continuous and interactive research similar to Earth-based laboratories. Because of these capabilities, the ISS is an indispensible laboratory for low gravity research. NASA GRC has been actively involved in developing and operating facilities and experiments on the ISS since the beginning of a permanent human presence on November 2, 2000. As the lead Center for combustion, complex fluids, and fluid physics; GRC has led the successful implementation of the Combustion Integrated Rack (CIR) and the Fluids Integrated Rack (FIR) as well as the continued use of other facilities on the ISS. These facilities have supported combustion experiments in fundamental droplet combustion; fire detection; fire extinguishment; soot phenomena; flame liftoff and stability; and material flammability. The fluids experiments have studied capillary flow; magneto-rheological fluids; colloidal systems; extensional rheology; pool and nucleate boiling phenomena. In this paper, we provide an overview of the experiments conducted on the ISS over the past 12 years.
Motil, Brian↗
Priorities for Microgravity Fluid Physics Research and An Overview of Gravity-Dependent Complex Fluids Research
No abstract available
Motil, Brian J.↗
Optical tweezer measurements of asymptotic nonlinearities in complex fluids
This article presents micro-medium-amplitude oscillatory shear (μMAOS), a method to measure the frequency-dependent micromechanical properties of soft materials in the asymptotically nonlinear regime using optical tweezers. For this work, we have developed a theoretical framework to extract these nonlinear mechanical properties of the material from experimental measurements and also proposed a physical interpretation of the third-order nonlinearities measured in single-tone oscillatory tests. We validate the method using a well-characterized surfactant solution of wormlike micelles, and subsequently employ this technique to demonstrate that the cytoplasm of a living cell undergoes strain softening and shear thinning when locally subjected to weakly nonlinear oscillatory deformations.
59 BASIC BIOLOGICAL SCIENCES↗
Complex Fluid‐Driven Fractures Caused by Crack‐Parallel Stress
Abstract Managing fluid‐driven fracture networks is crucial for subsurface resource utilization, yet the current understanding of the key controlling factors remains insufficient. While geologic discontinuities have been shown to significantly influence fracture network complexity, this study identifies another major contributor. We conducted a new set of experiments using a transparent true triaxial cell, which enabled video recording of the temporal evolution of fluid‐driven fracture paths. Using pseudo‐2D samples without macroscale structural discontinuities, we observed multiple occurrences of hydraulic fracture curving and branching under anisotropic boundary stresses. We proposed a theoretical model demonstrating that the stress parallel to the crack line in the solid matrix near the crack tip (i.e., the T ‐stress) accounts for the observed fracture curving behavior. This finding suggests that T ‐stress is an additional mechanism contributing to the complexity of fluid‐driven fracture networks in the subsurface, besides the geologic discontinuities.
58 GEOSCIENCES↗
Efficient numerical techniques for complex fluid flows
The aim of the present research program is the development of more efficient and reliable calculation schemes for the coupled momentum and continuity equations. The resulting schemes would significantly reduce the expense of computing complex flows such as those in combustion chambers, gas turbines, and heat exchangers.
Patankar, Suhas V.↗
Development of a pressure based multigrid solution method for complex fluid flows
In order to reduce the computational difficulty associated with a single grid (SG) solution procedure, the multigrid (MG) technique was identified as a useful means for improving the convergence rate of iterative methods. A full MG full approximation storage (FMG/FAS) algorithm is used to solve the incompressible recirculating flow problems in complex geometries. The algorithm is implemented in conjunction with a pressure correction staggered grid type of technique using the curvilinear coordinates. In order to show the performance of the method, two flow configurations, one a square cavity and the other a channel, are used as test problems. Comparisons are made between the iterations, equivalent work units, and CPU time. Besides showing that the MG method can yield substantial speed-up with wide variations in Reynolds number, grid distributions, and geometry, issues such as the convergence characteristics of different grid levels, the choice of convection schemes, and the effectiveness of the basic iteration smoothers are studied. An adaptive grid scheme is also combined with the MG procedure to explore the effects of grid resolution on the MG convergence rate as well as the numerical accuracy.
Shyy, Wei↗
Efficient numerical techniques for complex fluid flows
The central feature in any flow prediction method is the treatment of the coupling between the momentum and continuity equations. In natural-convection flows, the energy equation also becomes strongly coupled with the momentum equations. Because of the nonlinear nature of the coupling, these equations are solved iteratively. Iterative methods are often prone to slow convergence, divergence, and extreme sensitivity to underrelaxation factors. The aim of the present research is to develop more efficient and reliable solution schemes for the coupled flow equations. Such schemes will significantly reduce the expense of computing complex flows encountered in combustion chambers, gas turbines, heat exchangers, and other practical equipment. In the work completed so far, a technique employing norm reduction in conjunction with the successive-substitution and Newton-Raphson techniques was developed. Also, a block-correction procedure for the flow equations is currently being formulated and tested.
Patankar, Suhas V.↗
Experiences with explicit finite-difference schemes for complex fluid dynamics problems on STAR-100 and CYBER-203 computers
Several two- and three-dimensional external and internal flow problems solved on the STAR-100 and CYBER-203 vector processing computers are described. The flow field was described by the full Navier-Stokes equations which were then solved by explicit finite-difference algorithms. Problem results and computer system requirements are presented. Program organization and data base structure for three-dimensional computer codes which will eliminate or improve on page faulting, are discussed. Storage requirements for three-dimensional codes are reduced by calculating transformation metric data in each step. As a result, in-core grid points were increased in number by 50% to 150,000, with a 10% execution time increase. An assessment of current and future machine requirements shows that even on the CYBER-205 computer only a few problems can be solved realistically. Estimates reveal that the present situation is more storage limited than compute rate limited, but advancements in both storage and speed are essential to realistically calculate three-dimensional flow.
Kumar, A.↗
Error and Uncertainty Quantification in the Numerical Simulation of Complex Fluid Flows
The failure of numerical simulation to predict physical reality is often a direct consequence of the compounding effects of numerical error arising from finite-dimensional approximation and physical model uncertainty resulting from inexact knowledge and/or statistical representation. In this topical lecture, we briefly review systematic theories for quantifying numerical errors and restricted forms of model uncertainty occurring in simulations of fluid flow. A goal of this lecture is to elucidate both positive and negative aspects of applying these theories to practical fluid flow problems. Finite-element and finite-volume calculations of subsonic and hypersonic fluid flow are presented to contrast the differing roles of numerical error and model uncertainty. for these problems.
Barth, Timothy J.↗
Physical Science Informatics: Providing Open Science Access to Microheater Array Boiling Experiment Data
The Physical Science Informatics (PSI) system is the next step in this an effort to make NASA sponsored flight data available to the scientific and engineering community, along with the general public. The experimental data, from six overall disciplines, Combustion Science, Fluid Physics, Complex Fluids, Fundamental Physics, and Materials Science, will present some unique challenges. Besides data in textual or numerical format, large portions of both the raw and analyzed data for many of these experiments are digital images and video, requiring large data storage requirements. In addition, the accessible data will include experiment design and engineering data (including applicable drawings), any analytical or numerical models, publications, reports, and patents, and any commercial products developed as a result of the research. This objective of paper includes the following: Present the preliminary layout (Figure 2) of MABE data within the PSI database. Obtain feedback on the layout. Present the procedure to obtain access to this database.
nucleate boiling↗
Novel Biomedical Device Utilizing Light-Emitting Nanostructures Developed
Sketches and chemical diagrams of state-of-the-art device and novel proposed device are presented. Current device uses a diode laser that emits into a fluorescent fluid only one wavelength and a photodetector diode that detects only one wavelength. Only one type of bacteria can be detected. The proposed device uses a quantum dot array that emits into a fluorescent fluid multiple wavelengths and an NIR 512 spectrometer that scans 0.8- to 1.7-mm wavelengths. Hundreds of different bacteria and viruses can be detected. A novel biomedical device is being developed at the NASA Glenn Research Center in cooperation with the University of Michigan. This device uses nano-structured quantum dots that emit light in the near-infrared (IR) region. The nanostructured quantum dots are used as a source and excite fluorochrome polymers coupled with antibodies that seek out and attach to specific bacteria and viruses. The fluorochrome polymers/antibodies fluoresce at specific wavelengths in the near-IR spectrum, but these wavelengths are offset from the excitation wavelength and can be detected with a tunable spectrometer. The device will be used to detect the presence of viruses and bacteria in simple fluids and eventually in more complex fluids, such as blood. Current state-of-the-art devices are limited to single bacteria or virus detection and a considerable amount of time and effort is required to prepare samples for analysis. Most importantly, the devices are quite large and cumbersome, which prohibits them from being used on the International Space Station and the space shuttles. This novel device uses nanostructured quantum dots which, through molecular beam epitaxy and highly selective annealing processes, can be developed into an illumination source that could potentially generate hundreds of specific wavelengths. As a result, this device will be able to excite hundreds of antibody/fluorochrome polymer combinations, which in turn could be used to detect hundreds of bacteria and viruses in fluids. A novel sample preparation technique that exploits micromembrane filtration and centrifugation methods has been developed for this device. The technique greatly reduces the time required to prepare the sample and the amount of sample needed to perform an accurate and comprehensive analysis. Last, and probably most important, because of the nano-light-emitting source and the novel sample preparation technique, the overall size of the device could be reduced dramatically. This device will serve as a nanoscale lab-on-a-chip for in situ microorganism detection and will enable tests to be performed on a time scale of minutes rather than days. Thus, it is ideally suited for monitoring the environmental conditions onboard the International Space Station and the space shuttles, thereby enhancing the safety of the astronauts. In addition, the device has important commercial applications, such as detecting the presence of bacteria and viruses in water at food- and beverage-processing centers, water treatment plants, and restaurants. Also, this technology has the potential to be used to detect bacteria and viruses in more complex fluids, such as blood--which in all likelihood would revolutionize blood analysis as it is performed today. This project was made possible through the Director's Discretionary Fund and is ongoing. In addition, this project provides funding to Dr. Rachel Goldman of the University of Michigan for the research and development of nanostructured quantum dots.
Scardelletti, Maximilian C.↗