tapsap.transient_analysis package
Submodules
tapsap.transient_analysis.concentration_g module
- tapsap.transient_analysis.concentration_g.concentration_g(flux: ndarray, times: ndarray, zone_lengths: dict) ndarray
Calculation of the concentration via the G-Procedure.
- Args:
flux (float ndarray): The outlet flux.
times (float ndarray): An array of time.
zone_lengths (dict): The reactor zone lengths.
- Returns:
concentration (float ndarray): The gas concentration (1/second) of the given flux.
- Citation:
Yablonsky et al, “The Y-procedure: How to extract the chemical transformation rate from reaction–diffusion data with no assumption on the kinetic model”
Redekop et al, “The Y-Procedure methodology for the interpretation of transient kinetic data: Analysis of irreversible adsorption”
Kunz et al, “Pulse response analysis using the Y-procedure: A data science approach”
Kunz et al, “Probability theory for inverse diffusion: Extracting the transport/kinetic time-dependence from transient experiments”
- Implementor:
Ross Kunz
- See also:
tapsap.utils.trapz
- Link:
https://doi.org/10.1016/j.ces.2007.04.050
https://doi.org/10.1016/j.ces.2011.08.055
tapsap.transient_analysis.concentration_units module
- tapsap.transient_analysis.concentration_units.concentration_units(gas_diffusion: float, zone_lengths: dict, reactor_radius: float, mol_per_pulse: float = 1) float
Calculation of the concentration units: (mol per pulse * catalyst zone length) / (gas diffusion * cross sectional area). This results in the concentration returned as mol/m3. Note: the units in meters is dependent on the user input of the diffusion coefficient and zone length units. For example, if the length units are given as cm, then the resulting concentration will be given as mol / cm3.
- Args:
gas_diffusion (float): The diffusion coefficient of the gas.
zone_lengths (dict): The reactor zone lengths.
reactor_radius(float): The radius of the reactor.
mol_per_pulse (float): The mol per injection.
- Returns:
units (float): The gas concentration units (mol/m3).
- Citation:
Yablonsky et al, “The Y-procedure: How to extract the chemical transformation rate from reaction–diffusion data with no assumption on the kinetic model”
Redekop et al, “The Y-Procedure methodology for the interpretation of transient kinetic data: Analysis of irreversible adsorption”
Kunz et al, “Pulse response analysis using the Y-procedure: A data science approach”
Kunz et al, “Probability theory for inverse diffusion: Extracting the transport/kinetic time-dependence from transient experiments”
- Implementor:
Ross Kunz
- Link:
https://doi.org/10.1016/j.ces.2007.04.050
https://doi.org/10.1016/j.ces.2011.08.055
tapsap.transient_analysis.concentration_y module
- tapsap.transient_analysis.concentration_y.concentration_y(flux: ndarray, times: ndarray, diffusion: float, zone_lengths: dict, zone_porosity: dict, smoothing_amt: float = 3) ndarray
Calculation of the concentration via the Y-Procedure. Note that they Y-Procedure is extremely sensitive on the smoothing amount provided.
- Args:
flux (float ndarray): The outlet flux.
times (float ndarray): An array of time.
diffusion (float): The diffusion coefficient within the catalyst zone.
zone_lengths (dict): The reactor zone lengths.
zone_porosity (dict): The assumed bed porosity within the catalyst.
smoothing_amt (float, optional): The amount of smoothing to be applied to the Y-Procedure.
- Returns:
concentration (float ndarray): The gas concentration (1/second) of the given flux.
- Citation:
Yablonsky et al, “The Y-procedure: How to extract the chemical transformation rate from reaction–diffusion data with no assumption on the kinetic model”
Redekop et al, “The Y-Procedure methodology for the interpretation of transient kinetic data: Analysis of irreversible adsorption”
Kunz et al, “Pulse response analysis using the Y-procedure: A data science approach”
Kunz et al, “Probability theory for inverse diffusion: Extracting the transport/kinetic time-dependence from transient experiments”
- Implementor:
Ross Kunz
- Link:
https://doi.org/10.1016/j.ces.2007.04.050
https://doi.org/10.1016/j.ces.2011.08.055
tapsap.transient_analysis.postprocess_g module
- tapsap.transient_analysis.postprocess_g.postprocess_g(flux: ndarray, flux_argmax: Optional[int] = None) ndarray
Correction of negative values within the concentration and rate via the G-Procedure due to noise early within the flux.
- Args:
flux (float ndarray): The outlet flux. More specifically, the concentration or rate.
flux_argmax (float, optional): The index of the maximum of the flux (typically the flux not the concentration or rate).
- Returns:
flux (float ndarray): The flux without the negative values before the maximum of the flux response.
- Citation:
None
- Implementor:
Ross Kunz
- See also:
None
- Link:
None
tapsap.transient_analysis.rate_g module
- tapsap.transient_analysis.rate_g.rate_g(flux: ndarray, times: ndarray, zone_lengths: dict, inert_flux: Optional[ndarray] = None) ndarray
Calculation of the rate via the G-Procedure. If the flux is derived from the reactant gas, then flux must be the difference of the inert_flux and reactant_flux or inert_flux must be populated with the flux of the inert.
- Args:
flux (float ndarray): The outlet flux.
times (float ndarray): An array of time.
zone_lengths (dict): The reactor zone lengths.
inert_flux (float ndarray, optional): The outlet flux of the inert.
- Returns:
rate (float ndarray): The gas rate (temporal) of the given flux.
- Citation:
Yablonsky et al, “The Y-procedure: How to extract the chemical transformation rate from reaction–diffusion data with no assumption on the kinetic model”
Redekop et al, “The Y-Procedure methodology for the interpretation of transient kinetic data: Analysis of irreversible adsorption”
Kunz et al, “Pulse response analysis using the Y-procedure: A data science approach”
Kunz et al, “Probability theory for inverse diffusion: Extracting the transport/kinetic time-dependence from transient experiments”
- Implementor:
Ross Kunz
- See also:
tapsap.utils.trapz
- Link:
https://doi.org/10.1016/j.ces.2007.04.050
https://doi.org/10.1016/j.ces.2011.08.055
tapsap.transient_analysis.rate_units module
- tapsap.transient_analysis.rate_units.rate_units(mol_per_pulse: float = 1, catalyst_weight: float = 1) float
Calculation of the rate units: mol / catalyst weight. This results in the concentration returned as mol/m2/s. Note: the units in meters is dependent on the user input catalyst weight units.
- Args:
mol_per_pulse (float): The mol per injection.
catalyst_weight (float): The weight of the catalyst
- Returns:
units (float): The units units (mol/m2/s).
- Citation:
Yablonsky et al, “The Y-procedure: How to extract the chemical transformation rate from reaction–diffusion data with no assumption on the kinetic model”
Redekop et al, “The Y-Procedure methodology for the interpretation of transient kinetic data: Analysis of irreversible adsorption”
Kunz et al, “Pulse response analysis using the Y-procedure: A data science approach”
Kunz et al, “Probability theory for inverse diffusion: Extracting the transport/kinetic time-dependence from transient experiments”
- Implementor:
Ross Kunz
- Link:
https://doi.org/10.1016/j.ces.2007.04.050
https://doi.org/10.1016/j.ces.2011.08.055
tapsap.transient_analysis.rate_y module
- tapsap.transient_analysis.rate_y.rate_y(flux: ndarray, times: ndarray, diffusion: float, zone_lengths: dict, zone_porosity: dict, inert_flux: Optional[ndarray] = None, smoothing_amt: float = 3) ndarray
Calculation of the rate via the Y-Procedure. Note that they Y-Procedure is extremely sensitive on the smoothing amount provided.
- Args:
flux (float ndarray): The outlet flux.
times (float ndarray): An array of time.
diffusion (float): The diffusion coefficient within the catalyst zone.
zone_lengths (dict): The reactor zone lengths.
inert_flux (float ndarray, optional): The outlet flux of the inert.
smoothing_amt (float, optional): The amount of smoothing to be applied to the Y-Procedure.
zone_porosity (dict): The assumed bed porosity within the catalyst.
- Returns:
rate (float ndarray): The gas rate (temporal) of the given flux.
- Citation:
Yablonsky et al, “The Y-procedure: How to extract the chemical transformation rate from reaction–diffusion data with no assumption on the kinetic model”
Redekop et al, “The Y-Procedure methodology for the interpretation of transient kinetic data: Analysis of irreversible adsorption”
Kunz et al, “Pulse response analysis using the Y-procedure: A data science approach”
Kunz et al, “Probability theory for inverse diffusion: Extracting the transport/kinetic time-dependence from transient experiments”
- Implementor:
Ross Kunz
- Link:
https://doi.org/10.1016/j.ces.2007.04.050
https://doi.org/10.1016/j.ces.2011.08.055
tapsap.transient_analysis.uptake module
- tapsap.transient_analysis.uptake.uptake(rate: ndarray, times: ndarray) ndarray
Calculation of the uptake as the cumulative integral of the rate. The rate can be given from previous calculations or by the Y or G Procedure
- Args:
rate (float ndarray): The gas rate (temporal) of the given flux.
times (float ndarray): An array of time.
- Returns:
uptake (float ndarray): The uptake (temporal) of the given rate.
- Citation:
Yablonsky et al, “The Y-procedure: How to extract the chemical transformation rate from reaction–diffusion data with no assumption on the kinetic model”
Redekop et al, “The Y-Procedure methodology for the interpretation of transient kinetic data: Analysis of irreversible adsorption”
Kunz et al, “Pulse response analysis using the Y-procedure: A data science approach”
- Implementor:
Ross Kunz
- Link:
https://doi.org/10.1016/j.ces.2007.04.050