Model-based Design Strategy Research Articles

A population balance model for cosmetic emulsion design: A multiscale approach

The present study describes the relationship between operating conditions, product formulation, and product properties at different time and spatial scales applying a multiscale approach to the design of cosmetic emulsions. The study couples the rheological and textural properties of cosmetic emulsions, product formulation, and operating conditions with the drop size distribution (DSD) through the implementation of a Population Balance Model (PBM). The results indicate that the adjustable parameters of the PBM can be related to product formulation and operating conditions, which allows for the incorporation of emulsified product DSD in model-based design strategies. Empirical relationships for the model adjustable parameters of the model were proposed, allowing the application of the PBM over the experimental thickener concentration and agitation rate ranges. These relationships indicate that PBM can be coupled to the integrated emulsified product and process design, enabling the optimization of the production process, and enhancing the final product's quality.

JANUS: an open-source 3D printable perfusion bioreactor and numerical model-based design strategy for tissue engineering.

Bioreactors have been employed in tissue engineering to sustain longer and larger cell cultures, managing nutrient transfer and waste removal. Multiple designs have been developed, integrating sensor and stimulation technologies to improve cellular responses, such as proliferation and differentiation. The variability in bioreactor design, stimulation protocols, and cell culture conditions hampered comparison and replicability, possibly hiding biological evidence. This work proposes an open-source 3D printable design for a perfusion bioreactor and a numerical model-driven protocol development strategy for improved cell culture control. This bioreactor can simultaneously deliver capacitive-coupled electric field and fluid-induced shear stress stimulation, both stimulation systems were validated experimentally and in agreement with numerical predictions. A preliminary in vitro validation confirmed the suitability of the developed bioreactor to sustain viable cell cultures. The outputs from this strategy, physical and virtual, are openly available and can be used to improve comparison, replicability, and control in tissue engineering applications.

Application of Model-Based Systems Engineering for the Integration of Electric Engines in Electrified Aircraft

The objective of green, carbon-neutral flights is propelling the innovation of newer propulsion systems. With this increased development of an interdisciplinary form of propulsion for aircraft, the integration burdens and efforts intensify. In literature, it is estimated that it takes 10-15 years to design and develop an aircraft. The expected date of entry for any hybrid electric aircraft is 2035-2040. Any innovation and effort to cut this time by any degree should be explored and analysed. One of the techniques that have the potential to help fast-track the research and development of interdisciplinary systems is Model-based System Engineering (MBSE). Various studies have shown the benefit of employing a model-based design strategy. The focus case study relates to the integration of the electric machine and the propeller, along with related sub-systems. For Hybrid Electric Propulsion (HEP), the electric machine and propeller need to be integrated and their interaction to be analysed. MBSE is proposed as a methodology that would help streamline the process of design and integration of the two systems. This study documents the exploration of connecting MBSE with current simulation and modelling of sub-systems in order to ensure the fulfilment of stakeholder needs and full system effectiveness. This paper establishes the research problem, and the approach to be pursued, and gives notice of first developments and expected follow-up work.

Data-driven Output Regulation via Gaussian Processes and Luenberger Internal Models

This paper deals with the problem of adaptive output regulation for multivariable nonlinear systems by presenting a learning-based adaptive internal model-based design strategy. The approach builds on the recently proposed adaptive internal model design techniques based on the theory of nonlinear Luenberger observers, and the adaptation side is approached as a probabilistic regression problem. Unlike the previous approaches in the field, here only coarse assumptions about the friend structure are required, making the proposed approach suitable for applications where the exosystem is highly uncertain. The paper presents performance bounds on the attained regulation error and numerical simulations showing how the proposed method outperforms previous approaches.

Tailoring early-phase clinical trial design to address multiple research objectives.

In contemporary oncology drug development, implementation of novel early-phase designs with the ability to address multiple research objectives is needed to better refine regimens. This paper describes an adaptive design strategy for identifying a range of optimal regimens based on two endpoints within multiple cohorts. The proposed design was developed to address objectives in an early-phase trial of cancer vaccines in combination with agonistic antibodies to CD40 and CD27. We describe a model-based design strategy that was developed for a trial evaluating the safety and immunogenicity of vaccination with (1) peptides plus CD40 antibody and TLR3 ligand, (2) systemic administration of an agonistic CD27 antibody, and (3) to assess immune response from (1) and (2) compared to optimal controls in participants with stage IIB-IV melanoma. The proposed design is a practical adaptive method for use with combined immunotherapy regimens with multiple objectives within multiple cohorts of interest. Further advances in the effectiveness of cancer immunotherapies will require new approaches that include redefining optimal strategies to take multiple regimens forward into later phases, incorporating additional endpoints in the dose selection process and testing drug combination therapies to improve efficacy and reduce toxicity. Our goal is to facilitate the acceptance and application of more novel designs in contemporary early development trials.

IBioSim 3: A Tool for Model-Based Genetic Circuit Design.

The iBioSim tool has been developed to facilitate the design of genetic circuits via a model-based design strategy. This paper illustrates the new features incorporated into the tool for DNA circuit design, design analysis, and design synthesis, all of which can be used in a workflow for the systematic construction of new genetic circuits.

Model-based design of bistable cell factories for metabolic engineering.

Metabolism can exhibit dynamic phenomena like bistability due to the presence of regulatory motifs like the positive feedback loop. As cell factories, microorganisms with bistable metabolism can have a high and a low product flux at the two stable steady states, respectively. The exclusion of metabolic regulation and network dynamics limits the ability of pseudo-steady state stoichiometric models to detect the presence of bistability, and reliably assess the outcomes of design perturbations to metabolic networks. Using kinetic models of metabolism, we assess the change in the bistable characteristics of the network, and suggest designs based on perturbations to the positive feedback loop to enable the network to produce at its theoretical maximum rate. We show that the most optimal production design in parameter space, for a small bistable metabolic network, may exist at the boundary of the bistable region separating it from the monostable region of low product fluxes. The results of our analysis can be broadly applied to other bistable metabolic networks with similar positive feedback network topologies. This can complement existing model-based design strategies by providing a smaller number of feasible designs that need to be tested in vivo. http://lmse.biozone.utoronto.ca/downloads/. krishna.mahadevan@utoronto.ca. Supplementary data are available at Bioinformatics online.

Optimal Design of Integrated SMB-Crystallization Hybrid Separation Process Using a Binary Solvent

Hybrid separation processes combining simulated moving bed chromatography and crystallization have been known to reduce the capital cost for enantiomer separation, but past studies have been limited to systems of single-component pure solvent. In this study, a model-based design strategy using a binary solvent is presented. Separation of d- and l-phenylalanine in a mixture of methanol and water was employed as a case study. Experimental data for solid–liquid equilibrium as well as chromatographic separation were obtained at various compositions of the solvent mixture to model the process. The experimental data were used to model and optimize the design of the hybrid separation process. The trade-offs between the solubility, temperature, chromatographic separation, and eutectic compositions were analyzed using the model-based optimization approach. In a case study, it was found that the productivity can be increased by over 18% when the temperature is increased from 10 to 50 °C because of the lower eutectic purity.

Model-Based Design To Push the Boundaries of Sequence Control

An innovative model-based design strategy to synthesize well-defined sequence-controlled polymers is presented, enabling selection of both the most appropriate mediating agent and reaction conditions. In combination with experimental analysis, advanced kinetic Monte Carlo simulations are conducted, allowing a visualization of the connectivity of all monomer units of ca. 105 individual copolymer chains. The product quality can therefore be uniquely and unambiguously predicted for the first time at the molecular level, explicitly accounting for chain-to-chain deviations. The strategy is illustrated for BlocBuilder MA-initiated nitroxide-mediated polymerization, with styrene and N-benzylmaleimide as comomomers, and is generally applicable for all reversible deactivation radical polymerization (RDRP) techniques. Further design of the nitroxide-mediating capabilities and the reaction conditions allows the realization of a targeted (multi)functionalization pattern, including an increase of the contribution of t...

Rational design of temperature swing adsorption cycles for post-combustion CO2 capture

The design of temperature swing adsorption (TSA) cycles aimed at recovering the heavy product at high purity is investigated by model-based design and applied to the capture of CO2 from flue gases. This model based design strategy and an extensive parametric analysis enables gaining an understanding of how individual steps within TSA cycles affect the achievable purity and recovery of the CO2 product. This insight is used to evaluate three novel TSA cycle configurations by assessing them based on their productivity and energy consumption. The influence of heat integration, cycle scheduling and an external drying step on the performance of the cycles is systematically evaluated. This detailed analysis reveals the importance of the cycle configuration and provides a basis to rationally design TSA cycles for post-combustion CO2 capture. Using a commercial zeolite 13X adsorbent our novel TSA cycle design achieves for the first time CO2 capture and storage specifications (96% CO2 purity and 90% recovery) with moderate heating temperatures of up to 420K while avoiding the use of compression or vacuum. The specific energy consumption and productivity of this cycle are similar to amine-based absorption processes. The obtained results demonstrate the feasibility of TSA based processes for post-combustion CO2 capture applications, and the presented methodology can be used to evaluate and quantify possible improvements provided by using novel technology elements such as alternative materials.

A low cost, large area light soaking and testing station

AbstractTest stations for accelerated aging tests are crucial in the development of commercial solar panel manufacturing technologies. Such test‐beds must provide a reasonably uniform flux whose spectral distribution is an acceptable match to the solar spectrum. This work outlines the detailed design on a low cost test system based on metal‐ halide lamps that can deliver a simulated solar flux of up to 3 suns on a 100 cm by 100 cm square area with an intensity variation of around 15%. A total of 9 metal‐halide lamps, each rated at 1000 W, is placed on top an enclosure which has a sample holding table whose distance to the lamps can be adjusted anywhere between 10 cm and 70 cm. A series of fans, blow ambient air over the panels being tested in order to maintain surface temperatures. The system is complemented by the necessary instrumentation to capture IV curves simultaneously for up to 8 solar devices. A model based design strategy is adopted during the construction of the test station in order to predict and optimize the light distribution as well as the thermal behaviour. Sample IV data from commercial thin film Si solar cells are reported to demonstrate the stability of operation. The cost of the entire system is below $ 20,000, with most of the budget going towards the data acquisition hardware. (© 2015 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

Cortical hot spots and labyrinths: why cortical neuromodulation for episodic migraine with aura should be personalized

Stimulation protocols for medical devices should be rationally designed. For episodic migraine with aura we outline model-based design strategies toward preventive and acute therapies using stereotactic cortical neuromodulation. To this end, we regard a localized spreading depression (SD) wave segment as a central element in migraine pathophysiology. To describe nucleation and propagation features of the SD wave segment, we define the new concepts of cortical hot spots and labyrinths, respectively. In particular, we firstly focus exclusively on curvature-induced dynamical properties by studying a generic reaction-diffusion model of SD on the folded cortical surface. This surface is described with increasing level of details, including finally personalized simulations using patient's magnetic resonance imaging (MRI) scanner readings. At this stage, the only relevant factor that can modulate nucleation and propagation paths is the Gaussian curvature, which has the advantage of being rather readily accessible by MRI. We conclude with discussing further anatomical factors, such as areal, laminar, and cellular heterogeneity, that in addition to and in relation to Gaussian curvature determine the generalized concept of cortical hot spots and labyrinths as target structures for neuromodulation. Our numerical simulations suggest that these target structures are like fingerprints, they are individual features of each migraine sufferer. The goal in the future will be to provide individualized neural tissue simulations. These simulations should predict the clinical data and therefore can also serve as a test bed for exploring stereotactic cortical neuromodulation.

Model-based PID control of a Dielectric Electro-Active Polymer Positioning System

Abstract This paper considers a micrometric positioning system based on a dielectric electro-active polymer membrane. The motion is generated by the deformation of the membrane caused by the electrostatic compressive force between two compliant electrodes applied on the surface of the polymer. The paper suggests various model-based design strategies (in both time and frequency domains) for PID control laws, which are able to compensate the nonlinear behavior of the actuator (caused by the characteristics of the material and the annular geometry of the membrane) and obtain very precise tracking of steps or sinusoidal reference signals. The various design strategies are discussed and compared both in simulations and experiments.