49 research outputs found
Computational analysis of a 9D model for a small DRG neuron
Small dorsal root ganglion (DRG) neurons are primary nociceptors which are
responsible for sensing pain. Elucidation of their dynamics is essential for
understanding and controlling pain. To this end, we present a numerical
bifurcation analysis of a small DRG neuron model in this paper. The model is of
Hodgkin-Huxley type and has 9 state variables. It consists of a
Na1.7 and a Na1.8 sodium channel, a leak channel, a
delayed rectifier potassium and an A-type transient potassium channel. The
dynamics of this model strongly depends on the maximal conductances of the
voltage-gated ion channels and the external current, which can be adjusted
experimentally. We show that the neuron dynamics are most sensitive to the
Na1.8 channel maximal conductance (). Numerical
bifurcation analysis shows that depending on and the external
current, different parameter regions can be identified with stable steady
states, periodic firing of action potentials, mixed-mode oscillations (MMOs),
and bistability between stable steady states and stable periodic firing of
action potentials. We illustrate and discuss the transitions between these
different regimes. We further analyze the behavior of MMOs. Within this region,
bifurcation analysis shows a sequence of isolated periodic solution branches
with one large action potential and a number of small amplitude peaks per
period. A closer inspection reveals more complex concatenated MMOs in between
these periodic MMOs branches, forming Farey sequences. Lastly, we also find
small solution windows with aperiodic oscillations, which seem to be chaotic.
The dynamical patterns found here as a function of different parameters contain
information of translational importance as their relation to pain sensation and
its intensity is a potential source of insight into controlling pain
Evaluation of possible improvements of forced periodically operated reactor in which methanol synthesis takes place – based on the Nonlinear Frequency Response analysis
The continuous industrial chemical processes are typically designed through steady-state conditions. Nevertheless, there is evidence that processes can be intensified by applying optimized forced periodic operation. Possible improvements in reactor performances caused by the implementation of forced periodic operation (FPO) can be successfully evaluated by applying a nonlinear frequency response (NFR) analysis, before experimental investigation. In this study, we will present the results of two case studies based on heterogeneously catalyzed methanol synthesis in a continuous stirred tank reactor (CSTR). The first is an isothermal case, and the second is a more complicated and more realistic, non-isothermal case.This is a paper for 15th International Conference on Applied Energy (ICAE2023), Dec. 3-7, 2023, Doha, Qata
Influence of drying conditions on process properties and parameter identification for continuous fluidized bed spray agglomeration
[EN] Agglomeration is a particle formulation process in which at least two primary particles are combined to form a new one. The growth of agglomerates depends on interactions of particles covered with wet spots that generated by depositions of binder droplets. This work experimentally compares the influence of external feed rate and sprayed binder content on product properties and process stability with internal separation at different drying conditions. Due to the identification of parameters a populations balance model (PBM) is developed. The PBM includes the agglomeration kernel function, which characterizes the kinetics, i.e. the rate at which primary particles build agglomerates.This publication was supported by the Center of Dynamic Systems (CDS), funded by the EU-programme ERDF (European Regional Development Fund).Strenzke, G.; Golovin, I.; Wegner, M.; Palis, S.; Bück, A.; Kienle, A.; Tsotsas, E. (2018). Influence of drying conditions on process properties and parameter identification for continuous fluidized bed spray agglomeration. En IDS 2018. 21st International Drying Symposium Proceedings. Editorial Universitat Politècnica de València. 579-586. https://doi.org/10.4995/IDS2018.2018.7319OCS57958
Evaluating the shape of input pertubation for forced periodic operation
Continuous chemical processes are typically designed to operate under steady state
conditions. However, there is strong evidence that an optimized forced periodic
operation possesses the potential to improve process performance [1]. More
demonstration examples are needed to promote such advanced concepts.
In this contribution we will present results for two case studies. The first reaction
investigated is the liquid phase hydrolysis of acetic anhydride performed in an adiabatic
continuous stirred tank reactor (CSTR). The second examples is the heterogeneously
catalysed gas phase synthesis of methanol performed in an isothermal and isobaric
CSTR. Our theoretical analysis exploits independently determined kinetic models of
these reactions [2, 3]. Besides performing numerical process simulations the Nonlinear
Frequency Response (NFR) method [4] is used. The magnitude of possible process
improvements depends on the applied strategy of forced periodic operation. Besides
the input to be perturbed (concentration, flowrate, temperature, …), the forcing
frequency and the forcing amplitude as well as the shape of the input modulation are
of relevance. In this contribution we will compare the input modulated as harmonic
(Fig 1a) and as a square wave function (“bang-bang”, Fig 1b). In order to use the NFR
method for the latter input function an approximation via Fourier series is applied [5, 6].
The results reveal improvements of easier to practically implement square wave inputs
for both examples considered, compared to harmonic modulation of inputs [5, 6]
Forced periodic operations of a chemical reactor for methanol synthesis – The search for the best scenario based on Nonlinear Frequency Response Method. Part II Simultaneous modulation of two inputs
The analysis of the potential to improve performance of a methanol synthesis reactor through forced periodical operations by Nonlinear Frequency Response method is presented. The methanol synthesis in an isothermal and isobaric lab-scale CSTR is considered. First, the analysis was performed for single input modulations (in Part I), which showed that significant improvements can't be achieved. Here, the study is extended to analysis of simultaneous modulations of two inputs. All possible input combinations (6 cases) are analysed and the optimal forcing parameters, maximizing the time-average methanol production, were determined. For all combinations the improvement is possible, but for some cases it is not significant. The highest improvement is predicted for simultaneous modulation of the inlet partial pressure of CO and the inlet volumetric flow rate. This case, for which it is possible to achieve up to 33.51 % of methanol production, is analysed it detail and optimized using multi-objective optimization.This is the peer-reviewed version of the article: Daliborka Nikolić, Carsten Seidel, Matthias Felischak, Tamara Miličić, Achim Kienle, Andreas Seidel-Morgenstern, Menka Petkovska, Forced periodic operations of a chemical reactor for methanol synthesis – the search for the best scenario based on Nonlinear Frequency Response Method. Part II Simultaneous modulation of two inputs, Chemical Engineering Science, 2022, 248, 117133, doi: [https://doi.org/10.1016/j.ces.2021.117133]The published version: [https://cer.ihtm.bg.ac.rs/handle/123456789/4816
Possible improvement of methanol synthesis exploiting forced periodic operation: Analysis using the Nonlinear Frequency Responce Method
Forced periodic operations, as one way of Process Intensification, can be used in order to achieve better performances of chemical reactors, in comparison to conventional steady-state operation. In this study the Nonlinear Frequency Response (NFR) method, a powerful analytical and approximate tool which gives an answer whether and under which conditions certain periodic operation would lead to improvement of process performance was used. The analysis was done for the methanol synthesis using a standard Cu/ZnO catalyst performed in an isothermal and isobaric lab-scale CSTR. At first the single input modulations were analysed. The inputs considered for periodic modulation are: partial pressures of each reactant in the feed stream and the total volumetric inlet flow-rate. The objective was to maximize the mean molar outlet flow-rate of methanol. The specific forcing parameters were optimized. The results of the NFR analysis showed that modulations of single inputs do not provide potential for significant improvements.
The study was extended to analysis of periodic operations with simultaneous modulations of two inputs. Six possible input combinations were analysed and the optimal forcing parameters which maximizing again the time-average methanol production were determined. For all combinations an improvement is possible, but for some cases it was found to be not significant. However, significant
improvements are predicted for a) simultaneous modulation of the partial pressure of CO2 in the feed steam and the volumetric inlet flow-rate and b) simultaneous modulation of the partial pressure of hydrogen (H2) and the volumetric inlet flow-rate [1, 2]. The highest improvement could be achieved for
simultaneous modulation of the inlet partial pressure of CO and the inlet volumetric flow rate.Online Seminar, 10 Jan - 13 Jan 2022, [https://www.we-heraeus-stiftung.de/veranstaltungen/seminare/2022/from-wind-and-solar-energy-to-chemical-energy-storage-understanding-and-engineering-catalysis-under-dynamic-conditions/main/
Stability of Combined Continuous Granulation and Agglomeration Processes in a Fluidized Bed with Sieve-Mill-Recycle
Particle formation in fluidized beds is widely applied in an industrial context for the solidification of liquids and size enlargement of granular materials. The two main size-enlargement mechanisms are layering growth and agglomeration. For continuous process configurations with sieve-mill-recycle and layering growth only, the occurrence of undesired self-sustained oscillations in the particle size distribution under certain process conditions is well-known. This contribution investigates the stability of the practically relevant process with additional particle agglomeration by means of a model-based numerical bifurcation analysis. It is shown that the occurrence of stable limit cycles is inhibited by an increased rate of particle agglomeration for a variety of different process conditions and different agglomeration kinetics. These results enhance the understanding of the agglomeration and layering growth dynamics and are relevant for the process design and operation
Stability of Combined Continuous Granulation and Agglomeration Processes in a Fluidized Bed with Sieve-Mill-Recycle
Particle formation in fluidized beds is widely applied in an industrial context for the solidification of liquids and size enlargement of granular materials. The two main size-enlargement mechanisms are layering growth and agglomeration. For continuous process configurations with sieve-mill-recycle and layering growth only, the occurrence of undesired self-sustained oscillations in the particle size distribution under certain process conditions is well-known. This contribution investigates the stability of the practically relevant process with additional particle agglomeration by means of a model-based numerical bifurcation analysis. It is shown that the occurrence of stable limit cycles is inhibited by an increased rate of particle agglomeration for a variety of different process conditions and different agglomeration kinetics. These results enhance the understanding of the agglomeration and layering growth dynamics and are relevant for the process design and operation