skip to main content


Title: Mathematical Modelling of Reactive Inks for Additive Manufacturing of Charged Membranes
Patterned charged membranes with engendered useful characteristics can offer selective transport of electrolytes. Chemical patterning across the membrane surface via a physical inkjet deposition process requires precise control of the reactive-ink formulation, which enables the introduction of charged functionality to the membrane. This study develops a new dynamic mathematical model for the primary step of the batch reactive-ink formulation considering an ink mixture of copper sulphate and ascorbic acid. Nonlinear least squares parameter estimation is performed to infer three kinetic model parameters by analysing data from nine dynamic experiments simultaneously. Global sensitivity and Fisher information matrix (FIM) analyses reveal only one kinetic parameter is identifiable from time-series pH measurements. The fitted model can capture the overall nonlinear dynamics of the batch reaction and works best for initial Cu2 + concentrations between 30 and 50 mM. Time-series Cu2 + or Cu+ concentration measurements are recommended in future experiments to elucidate the kinetics of reactive-ink formulation.  more » « less
Award ID(s):
1941596
NSF-PAR ID:
10403699
Author(s) / Creator(s):
; ; ; ; ;
Editor(s):
Yamashita, Y.; Kano, M.
Date Published:
Journal Name:
Computer aided chemical engineering
Volume:
49
ISSN:
2543-1331
Page Range / eLocation ID:
1063-1068
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract. Resazurin (Raz) and its reaction product resorufin (Rru) have increasingly been used as reactive tracers to quantify metabolic activity and hyporheic exchange in streams. Previous work has indicated that these compounds undergo sorption in stream sediments. We present laboratory experiments on Raz and Rru transport, sorption, and transformation, consisting of 4 column and 72 batch tests using 2 sediments with different physicochemical properties under neutral (pH = 7) and alkaline (pH = 9) conditions. The study aimed at identifying the key processes of reactive transport of Raz and Rru in streambed sediments and the experimental setup best suited for their determination. Data from column experiments were simulated by a travel-time-based model accounting for physical transport, equilibrium and kinetic sorption, and three first-order reactions. We derived the travel-time distributions directly from the breakthrough curve (BTC) of the conservative tracer, fluorescein, rather than from fitting an advective-dispersive transport model, and inferred from those distributions the transfer functions of Raz and Rru, which provided conclusive approximations of the measured BTCs. The most likely reactive transport parameters and their uncertainty were determined by a Markov chain–Monte Carlo approach. Sorption isotherms of both compounds were obtained from batch experiments. We found that kinetic sorption dominates sorption of both Raz and Rru, with characteristic timescales of sorption in the order of 12 to 298 min. Linear sorption models for both Raz and Rru appeared adequate for concentrations that are typically applied in field tracer tests. The proposed two-site sorption model helps to interpret transient tracer tests using the Raz–Rru system.

     
    more » « less
  2. Delta 3D printers can significantly increase throughput in additive manufacturing by enabling faster and more precise motion compared to conventional serial-axis 3D printers. Further improvements in motion speed and part quality can be realized through model-based feedforward vibration control, as demonstrated on serial-axis 3D printers. However, delta machines have not benefited from model-based controllers because of the difficulty in accurately modeling their position-dependent, coupled nonlinear dynamics. In this paper, we propose an efficient framework to obtain accurate linear parameter-varying models of delta 3D printers at any position within their workspace from a few frequency response measurements. We decompose the dynamics into two sub-models–(1) an experimentally-identified sub-model containing decoupled vibration dynamics; and (2) an analytically-derived sub-model containing coupled dynamics–which are combined into one using receptance coupling. We generalize the framework by extending the analytical model of (2) to account for differing mass profiles and dynamic models of the printer’s end-effector. Experiments demonstrate reasonably accurate predictions of the position-dependent dynamics of a commercial delta printer, augmented with a direct drive extruder, at various positions in its workspace. Note to Practitioners—This work aims to equip high-speed 3D printers, like delta machines, with model-based controllers to complement their speed with high-accuracy. Due to the coupled kinematic chains of the delta, complex control methodologies, some of which require real-time state measurements, are often used to achieve satisfactory control performance. Our modeling approach provides an efficient methodology for obtaining accurate linear models without the need for real-time measurements, thus enabling practitioners to design linear model-based feedforward controllers to achieve the high throughput and accuracy desired in additive manufacturing (AM). The models we develop in this paper are intended for use with feedforward vibration compensation methods, which can be beneficial for both industrial-scale AM machines that have high-powered servo motors and feedback controllers, as well as consumer-grade AM machines which use stepper motors in feedforward control. 
    more » « less
  3. Microbially Induced Calcite Precipitation (MICP) is a bio-mediated cementation process that uses microbial enzymatic activity to catalyze the precipitation of CaCO3 minerals on soil particle surfaces and contacts. Extensive research has focused on understanding various aspects of MICP-treated soils including soil behavioral enhancements and process reaction chemistry, however, almost no research has explored the permanence of bio-cemented geomaterials. As the technology matures, an improved understanding of the longevity of bio-cementation improved soils will be critical towards identifying favorable field applications, quantifying environmental impacts, and understanding their long-term performance. In this study, a series of batch experiments were performed to investigate the dissolution kinetics of CaCO3-based bio- cemented sands with the specific aim of incorporating these behaviors into geochemical models. All batch experiments involved previously bio-cemented poorly graded sands that were exposed to different dissolution treatments intended to explore the magnitude and rate of CaCO3 dissolution as a function of acid type, concentration, initial pH, and other factors. During experiments, changes in solution pH and calcium concentrations indicative of CaCO3 dissolution were monitored. After experiments, aqueous measurements were compared to those simulated using two different dissolution kinetic frameworks. While not exhaustive, the results of these experiments suggest that the dissolution behavior of bio-cementation can be well-approximated using existing chemically controlled kinetic models, particularly when surrounding solutions are more strongly buffered. 
    more » « less
  4. Brehm, Christoph ; Pandya, Shishir (Ed.)
    We have derived a 3-D kinetic-based discrete dynamic system (DDS) from the lattice Boltzmann equation (LBE) for incompressible flows through a Galerkin procedure. Expressed by a poor-man lattice Boltzmann equation (PMLBE), it involves five bifurcation parameters including relaxation time from the LBE, splitting factor of large and sub-grid motion scales, and wavevector components from the Fourier space. Numerical experiments have shown that the DDS can capture laminar behaviors of periodic, subharmonic, n-period, and quasi-periodic and turbulent behaviors of noisy periodic with harmonic, noisy subharmonic, noisy quasi-periodic, and broadband power spectra. In this work, we investigated the effects of bifurcation parameters on the capturing of the laminar and turbulent flows in terms of the convergence of time series and the pattern of power spectra. We have found that the 2nd order and 3rd order PMLBEs are both able to capture laminar and turbulent flow behaviors but the 2nd order DDS performs better with lower computation cost and more flow behaviors captured. With the specified ranges of the bifurcation parameters, we have identified two optimal bifurcation parameter sets for laminar and turbulent behaviors. Beyond this work, we are exploring the regime maps for a deeper understanding of the contributions of the bifurcation parameters to the capturing of laminar and turbulent behaviors. Surrogate models (to replace the PMLBE) are being developed using deep learning techniques to overcome the overwhelming computation cost for the regime maps. Meanwhile, the DDS is being employed in the large eddy simulation of turbulent pulsatile flows to provide dynamic sub-grid scale information. 
    more » « less
  5. null (Ed.)
    Parameter estimation for nonlinear dynamic system models, represented by ordinary differential equations (ODEs), using noisy and sparse data, is a vital task in many fields. We propose a fast and accurate method, manifold-constrained Gaussian process inference (MAGI), for this task. MAGI uses a Gaussian process model over time series data, explicitly conditioned on the manifold constraint that derivatives of the Gaussian process must satisfy the ODE system. By doing so, we completely bypass the need for numerical integration and achieve substantial savings in computational time. MAGI is also suitable for inference with unobserved system components, which often occur in real experiments. MAGI is distinct from existing approaches as we provide a principled statistical construction under a Bayesian framework, which incorporates the ODE system through the manifold constraint. We demonstrate the accuracy and speed of MAGI using realistic examples based on physical experiments. 
    more » « less