DECOLOG
6.0.1
(software last update 24/02/2022)
(software last update 24/02/2022)
Technical
Informations
(PDF manual old version 3.0)
DECOLOG Software Presentation
(May 2016 - PDF format 4.2MB)
Downloads DECOLOG software
(PDF manual old version 3.0)
DECOLOG Software Presentation
(May 2016 - PDF format 4.2MB)
Downloads DECOLOG software
Authors:
Lorenzo Borselli
Instituto de Geologia / Fac. De Ingegneria
Universitad Autonoma de San Luis Potosì,
Av. Dr. Manuel Nava 5, C.P. 78240 San Luis Potosí, S.L.P. UASLP (MEXICO), lborselli@gmail.com
https://www.lorenzo-borselli.eu
Damiano Sarocchi
Instituto de Geologia / Fac. De Ingegneria
Universitad Autonoma de San Luis Potosì,
Av. Dr. Manuel Nava 5, C.P. 78240 San Luis Potosí, S.L.P. UASLP (MEXICO), damiano.sarocchi@uaslp.mx
AND MORE FREEWARE RELATED SOFTWARE
AT WWW.LAIMA-UASLP.ORG
DECONVOLUTION
OF MIXTURE'S
COMPONENTS INSIDE
PARTICLE SIZE DISTRIBUTIONS
DECOLOG 6.0.1 COMPONENTS INSIDE
PARTICLE SIZE DISTRIBUTIONS
Win 64 bit , Portable App
(2004,2022)
(last update 14/01/2024)
CONACYT:
Proyectos Ciencia Basica:
CB-2012/184060, CB-2016/28676
CB-2012/184060, CB-2016/28676
What is
DECOLOG
Experimentally derived particle size distribution often shown multi-modal shape and this characteristic is usually interpreted as a mixture of two or more populations. The origin of these mixture has been commonly interpreted as due to the complex processes linked to the origin of the sediment ad clasts , to the transport and final deposition, or in other terms, the geological cycle of sediment transport and evolution, the weathering and soil process may affect the final distribution of particles present in the sampled deposit.
The basic idea is that the all the processes responsible of the deposit leave some trace of them inside the special characteristics of the mixture and their populations. We assume that the mixture maintains encoded in its the global distribution information.
Aim of DECOLOG software is develop a solution to decode the information present in the natural mixture of particles/sediments using, as paradigm, the Log-normal or Weibull distributions and particularly a defined mixture of these distributions.
Decolog performs this operation using innovative techniques of optimization and in automatic way, without the needs of special efforts from user, as the initial guessing of observed distribution's peaks .....
The easiness of use is one of the most innovative and appreciated characteristics of current version of DECOLOG
Experimentally derived particle size distribution often shown multi-modal shape and this characteristic is usually interpreted as a mixture of two or more populations. The origin of these mixture has been commonly interpreted as due to the complex processes linked to the origin of the sediment ad clasts , to the transport and final deposition, or in other terms, the geological cycle of sediment transport and evolution, the weathering and soil process may affect the final distribution of particles present in the sampled deposit.
The basic idea is that the all the processes responsible of the deposit leave some trace of them inside the special characteristics of the mixture and their populations. We assume that the mixture maintains encoded in its the global distribution information.
Aim of DECOLOG software is develop a solution to decode the information present in the natural mixture of particles/sediments using, as paradigm, the Log-normal or Weibull distributions and particularly a defined mixture of these distributions.
Decolog performs this operation using innovative techniques of optimization and in automatic way, without the needs of special efforts from user, as the initial guessing of observed distribution's peaks .....
The easiness of use is one of the most innovative and appreciated characteristics of current version of DECOLOG
DECOLOG 6.0 main
window (click on the image to enlarge)
Please note: now is
possible download the DECOLOG version 6.0.1
(64 bit) at the download page.. the
documentation isn't updated. will be updated
soon.. The release 6.0.1 contains
important improvements and in particular now
DECOLOG code is released only in the
Win 64 bit version.
The release 6.0.1 (64 bit) of DECOLOG may be run only in Windows 7 ,8x and 10,11 64 bit CPU. The the DECOLOG optimization engines allow to consider components (Lognormal or Weibull distributions) with negative skewness (so left tailed). To do that we use generalized 4 parameters Lognormal or Weibull distributions. DECOLOG 6.0.1 can now decode now until to 4 mixture's components. DECOLOG 6.0.1can manage even or uneven observed distribution's bins. A new test was included in DECOLOG 6.0.1. The test launched before optimization processing, avoids to run optimization in case of Insufficient degree of freedom and thus it contribute to avoid overfitting.
The internal optimization engine of DECOLOG has been greatly improved using last findings in Multi-Objective optimization algorithms based on Differential evolution (DE) + FSADE algorithms. That’s improving the speed of convergence,reliability and reproducibility of final results. The new TDE optimization engine has been also implemented since 2009 in DECOLOG software.
In the updated version 6.0.1 now DECOLOG can be installed in any drive or directory of your HD or USB key. Decolog is a full PORTABLE app. As well data to be processed can be stored in any path of your windows system..(see Download page for special instruction for installation)
Enjoy DECOLOG...!!
The release 6.0.1 (64 bit) of DECOLOG may be run only in Windows 7 ,8x and 10,11 64 bit CPU. The the DECOLOG optimization engines allow to consider components (Lognormal or Weibull distributions) with negative skewness (so left tailed). To do that we use generalized 4 parameters Lognormal or Weibull distributions. DECOLOG 6.0.1 can now decode now until to 4 mixture's components. DECOLOG 6.0.1can manage even or uneven observed distribution's bins. A new test was included in DECOLOG 6.0.1. The test launched before optimization processing, avoids to run optimization in case of Insufficient degree of freedom and thus it contribute to avoid overfitting.
The internal optimization engine of DECOLOG has been greatly improved using last findings in Multi-Objective optimization algorithms based on Differential evolution (DE) + FSADE algorithms. That’s improving the speed of convergence,reliability and reproducibility of final results. The new TDE optimization engine has been also implemented since 2009 in DECOLOG software.
In the updated version 6.0.1 now DECOLOG can be installed in any drive or directory of your HD or USB key. Decolog is a full PORTABLE app. As well data to be processed can be stored in any path of your windows system..(see Download page for special instruction for installation)
Enjoy DECOLOG...!!
DECOLOG 6.0 in Windows 10
(click on the image to enlarge)
Credits
and LICENCE
CONACYT:
Proyecto Ciencia Basica CB-2012/184060
and
Proyecto Ciencia Basica CB-2016/286764
Free Pascal 3.2.2
CONACYT:
Proyecto Ciencia Basica CB-2012/184060
and
Proyecto Ciencia Basica CB-2016/286764
Free Pascal 3.2.2
This software is released as FREEWARE for the scientific community.
This imply that is released and downloadable for free, but without warranties .
The authors of this software want acknowledge the people that with their testing activities and suggestions helped us to improve the performance of DECOLOG.
All the Suggestions from the users are welcomed and greatly appreciated.
DECOLOG has been realised entirely in Object Pascal programming language, using:
FPC compiler,
LAZARUS IDE;
GDB debugger
A special credits to :
sumatraPDF (freeware PDF viewer)
Gnuplot (freeware grafic rendering engine)
Graphic
PDF output of DECOLOG 6.0 (click on the
image to enlarge)
Published Scientific
Peer Reviewed Papers where DECOLOG has been
used (last updated 14 january 2024):
- Bellotti, F., Capra, L., Sarocchi, D., & D'Antonio, M. (2010). Geostatistics and multivariate analysis as a tool to characterize volcaniclastic deposits: Application to Nevado de Toluca volcano, Mexico. Journal of volcanology and geothermal research, 191(1-2), 117-128.
- Bernard, B., Samaniego, P., Mastin, L., Hernandez, S., Pino, G., Kibler, J., ... & Vizuete, N. (2022). Forecasting and communicating the dispersion and fallout of ash during volcanic eruptions: lessons from the September 20, 2020 eruptive pulse at Sangay volcano, Ecuador. Frontiers in Earth Science, 10, 912835.
- Caballero, L., Sarocchi, D., Soto, E., & Borselli, L. (2014). Rheological changes induced by clast fragmentation in debris flows. Journal of Geophysical Research: Earth Surface, 119(9), 1800-1817.
- Capra, L., Sulpizio, R., Márquez-Ramirez, V. H., Coviello, V., Doronzo, D. M., Arambula-Mendoza, R., & Cruz, S. (2018). The anatomy of a pyroclastic density current: the 10 July 2015 event at Volcán de Colima (Mexico). Bulletin of Volcanology, 80, 1-14.
- Charbonnier, S. J., Garin, F., Rodríguez, L. A., Ayala, K., Cancel, S., Escobar-Wolf, R., ... & Calder, E. S. (2023). Unravelling the dynamics and hazards of the June 3rd, 2018, pyroclastic density currents at Fuego volcano (Guatemala). Journal of Volcanology and Geothermal Research, 436, 107791.
- Charbonnier, S. J., Germa, A., Connor, C. B., Gertisser, R., Preece, K., Komorowski, J. C., ... & Connor, L. (2013). Evaluation of the impact of the 2010 pyroclastic density currents at Merapi volcano from high-resolution satellite imagery, field investigations and numerical simulations. Journal of Volcanology and Geothermal Research, 261, 295-315.
- Chávez, G. M., Sarocchi, D., Santana, E. A., & Borselli, L. (2015). Optical granulometric analysis of sedimentary deposits by color segmentation-based software: OPTGRAN-CS. Computers & Geosciences, 85, 248-257.
- Eychenne, J., & Engwell, S. L. (2023). The grainsize of volcanic fall deposits: Spatial trends and physical controls. Bulletin, 135(7-8), 1844-1858.
- Eychenne, J., Cashman, K., Rust, A., & Durant, A. (2015). Impact of the lateral blast on the spatial pattern and grain size characteristics of the 18 May 1980 Mount St. Helens fallout deposit. Journal of Geophysical Research: Solid Earth, 120(9), 6018-6038.
- Gudnason, J., Thordarson, T., Houghton, B. F., & Larsen, G. (2018). The 1845 Hekla eruption: Grain-size characteristics of a tephra layer. Journal of Volcanology and Geothermal Research, 350, 33-46.
- Rodríguez-Sedano, L. A., Sarocchi, D., Caballero, L., Borselli, L., Ortiz-Rodríguez, A. J., Cerca-Ruiz, M. F., ... & Ramos, O. F. (2022). Post-eruptive lahars related to the 1913 eruption in La Lumbre Ravine, Volcán de Colima, Mexico: The influence of ravine morphometry on flow dynamics. Journal of Volcanology and Geothermal Research, 421, 107423.
- Sarocchi, D., Borselli, L., & Macías, J. L. (2008, October). New tools to investigate textures of pyroclastic deposits. In IOP Conference Series: Earth and Environmental Science (Vol. 3, No. 1, p. 012009). IOP Publishing.
- Sarocchi, D., Sulpizio, R. , Macías, J. L., & Saucedo, R. (2011). The 17 July 1999 block-and-ash flow (BAF) at Colima Volcano: new insights on volcanic granular flows from textural analysis. Journal of Volcanology and Geothermal Research, 204(1-4), 40-56.
- Saucedo, R., Macías, J. L., Sarocchi, D., Bursik, M., & Rupp, B. (2008). The rain-triggered Atenquique volcaniclastic debris flow of October 16, 1955 at Nevado de Colima Volcano, Mexico. Journal of Volcanology and Geothermal Research, 173(1-2), 69-83.
- Schmith, J., Höskuldsson, Á., Holm, P. M., & Larsen, G. (2018). Large explosive basaltic eruptions at Katla volcano, Iceland: Fragmentation, grain size and eruption dynamics. Journal of Volcanology and Geothermal Research, 354, 140-152.
- Tsuji, T., Nishizaka, N., & Ohnishi, K. (2020). Influence of particle aggregation on the tephra dispersal and sedimentation from the October 8, 2016, eruption of Aso volcano. Earth, Planets and Space, 72(1), 1-19.
- Vázquez, R., Capra, L., Caballero, L., Arámbula-Mendoza, R., & Reyes-Dávila, G. (2014). The anatomy of a lahar: Deciphering the 15th September 2012 lahar at Volcán de Colima, Mexico. Journal of Volcanology and Geothermal Research, 272, 126-136.