VPPD-Lab

Kalakul, Sawitree; Cignitti, Stefano; Zhang, Lei; Gani, Rafiqul

doi:10.1016/b978-0-444-63683-6.00003-4

Cited by 9 publications

(5 citation statements)

References 37 publications

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“…The property model equation details are given in the Appendix (Supporting Information). where x i is molar fraction of compound i in the mixture; P ij is the pure component property j of compound i ; p nk is nonlinear property K ; X is a vector of compositions; D is a vector of model parameters; UB is a upper bound value of the linear property; LB is a lower bound value of the linear property. Details of the model may be found in Yunus et al and Gani et al In step 3, a solution to the above MINLP problem is achieved via strategies such as database search; generate-test approach (first generate candidates that satisfy the constraints and then order the feasible candidates in terms of their objective function values); simultaneous solution approach (use an appropriate optimization algorithm to solve the MINLP problem); and decomposition approach (decompose the main problem into subproblems and solve these subproblems according to a predefined solution order). The computer-aided tools used in this step are highlighted in Figure .…”

Section: Methodsmentioning

confidence: 99%

Designing a Surrogate Fuel for Gas-to-Liquid Derived Diesel

Choudhury¹,

Intikhab²,

Kalakul

et al. 2017

Energy Fuels

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Synthetic diesel fuel produced from natural gas via gas-to-liquid (GTL) technology is referred to as ultraclean fuel but is still challenged for full certification as diesel fuel. GTL diesel lacks certain hydrocarbons and chemical constituents, which although are benign to the environment, result in a trade-off in performance when used in a diesel engine. To boost GTL diesel physicochemical properties and thereby enable its use in conventional diesel engines, GTL diesel needs improvement. This can be achieved by mixing suitable additives to the GTL diesel and through the development of surrogate fuels that have fewer components. Screening of thousands of additives is a tedious task and can be done efficiently via computer based modeling to quickly and reliably identify a small number of promising candidates. These models are used to guide the formulation of five surrogates and predict their physicochemical properties. These surrogates are further verified using rigorous mathematical tools as well as through advanced experimental techniques. An optimal surrogate MI-5 is identified, which closely mimics GTL diesel-conventional diesel blends in terms of its physicochemical properties. An engine study for the surrogate is also performed to understand the effect of physicochemical properties on combustion as well as the emission behavior of the fuel. MI-5 exhibited an optimal torque at higher load conditions. A reduction of 11.26% NOx emission for MI-5 is observed when compared to conventional fuel. At higher loads, diesel fuel surpasses the total hydrocarbon (THC) emissions for both the surrogate and the GTL fuel. No significant variation in CO and CO2 emissions for MI-5, GTL diesel and conventional diesel is observed. Analysis of combustion as well as emission behavior of the fuels helps to understand the role of physicochemical properties on the performance of the fuel.

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Section: Methodsmentioning

confidence: 99%

Designing a Surrogate Fuel for Gas-to-Liquid Derived Diesel

Choudhury¹,

Intikhab²,

Kalakul

et al. 2017

Energy Fuels

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“…Similarly, to a process simulator analyzing different chemical processes, the VPPD-Lab is able to design and analyze different chemical products. The VPPD-Lab is supported by tools, such as a property model library, a knowledge base, structured databases, and calculation routines, see the study reported by Kalakul et al [34] for more information. The software can be provided to universities by contacting the corresponding author.…”

Section: Software Tool (Methods and Tools)mentioning

confidence: 99%

Computer-aided design of formulated products

Kontogeorgis

Jhamb

Dam‐Johansen

2022

Current Opinion in Colloid & Interface Science

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“…The framework for the design of liquid based formulations developed by Conte et al 11 , which is integrated in a computer-aided framework called the virtual Product Process Design Laboratory, or the vPPD-Lab 51 , has been successfully applied to TiO2 -based coating formulation. The computer algorithm, MIXD developed in the aforementioned work for the systematic design of thermodynamically stable binary solvent mixtures, is an efficient and reliable method.…”

Section: Solvent Mixture Design For Formulationmentioning

confidence: 99%

“…Several tools based on property models and fundamentals in thermodynamics have been developed for coating formulation design. The CAMD and MIXD algorithms, mentioned in the previous section, are available via the ProCAMD tool of ICAS 56 and the vPPD-Lab tool 51 respectively, both developed at DTU Chemical Engineering. The generic architecture of the vPPD-Lab tool is shown in Figure 6.…”

Section: Computer-aided Tools For Formulation Designmentioning

confidence: 99%