Effect of recycle ratio on the cost of natural gas processing in countercurrent hollow fiber membrane system

S.S.M. Lock,K.K. Lau,A.M. Shariff 한국공업화학회 2015 Journal of Industrial and Engineering Chemistry Vol.21 No.1

The separation of the countercurrent hollow fiber membrane module has been characterized adapting a‘‘Multi-component Progressive Cell Balance’’ approach and incorporated within the Aspen HYSYSprocess simulator. The simulated data is found to exhibit good accordance with published experimentalresult. The study of the double staged membrane module with permeate recycle system, which wasproposed to be the optimum configuration in previous works, has been extended by altering the recycleratio of the permeate stream to study the process economics. Parameter sensitivities of typicalmembrane selectivity and CO2 feed concentration adapted in industrial application have beenconducted. The study of high CO2 content is highlighted since it represents the future expansion ofnatural gas extraction considering that most of the remaining fields contain high concentration. It isobserved that the recycle ratio is an important parameter to be considered in the industrial designprocess since it affects the gas processing cost significantly. Increasing the recycle ratio is proposed toincrease the membrane area and compressor power while improving the hydrocarbon recovery, withsubstantial impact observed at low selectivity membrane and high CO2 feed concentration. A tradeoffmust be determined among these parameters for determination of the optimal recycle ratio configuration.

The impact of parametrized convection on cloud feedback

Webb, Mark J.,Lock, Adrian P.,Bretherton, Christopher S.,Bony, Sandrine,Cole, Jason N. S.,Idelkadi, Abderrahmane,Kang, Sarah M.,Koshiro, Tsuyoshi,Kawai, Hideaki,Ogura, Tomoo,Roehrig, Romain,Shin, Yech The Royal Society Publishing 2015 Philosophical transactions. Series A, Mathematical Vol.373 No.2054

<P>We investigate the sensitivity of cloud feedbacks to the use of convective parametrizations by repeating the CMIP5/CFMIP-2 AMIP/AMIP + 4K uniform sea surface temperature perturbation experiments with 10 climate models which have had their convective parametrizations turned off. Previous studies have suggested that differences between parametrized convection schemes are a leading source of inter-model spread in cloud feedbacks. We find however that ‘ConvOff’ models with convection switched off have a similar overall range of cloud feedbacks compared with the standard configurations. Furthermore, applying a simple bias correction method to allow for differences in present-day global cloud radiative effects substantially reduces the differences between the cloud feedbacks with and without parametrized convection in the individual models. We conclude that, while parametrized convection influences the strength of the cloud feedbacks substantially in some models, other processes must also contribute substantially to the overall inter-model spread. The positive shortwave cloud feedbacks seen in the models in subtropical regimes associated with shallow clouds are still present in the ConvOff experiments. Inter-model spread in shortwave cloud feedback increases slightly in regimes associated with trade cumulus in the ConvOff experiments but is quite similar in the most stable subtropical regimes associated with stratocumulus clouds. Inter-model spread in longwave cloud feedbacks in strongly precipitating regions of the tropics is substantially reduced in the ConvOff experiments however, indicating a considerable local contribution from differences in the details of convective parametrizations. In both standard and ConvOff experiments, models with less mid-level cloud and less moist static energy near the top of the boundary layer tend to have more positive tropical cloud feedbacks. The role of non-convective processes in contributing to inter-model spread in cloud feedback is discussed.</P>

Hollow fiber membrane model for gas separation: Process simulation, experimental validation and module characteristics study

파이잔아흐마드,K.K. Lau,S.S.M. Lock,Sikander Rafiq,Asad Ullah Khan,이문용 한국공업화학회 2015 Journal of Industrial and Engineering Chemistry Vol.21 No.1

Conceptual process simulations and optimization are essential in the design, operation andtroubleshooting stages of a membrane-based gas separation system. Despite this, there are fewmathematicalmodels/tools associated with a hollow fiber membrane module available in a commercialprocess simulator. A mathematical model dealing with the hollow fiber module characteristics that canbe included within a commercial process simulator is needed to examine the performance andeconomics of a gas separation system. In this study, a hollow fiber membrane modelwas incorporated inAspen HYSYS as a user defined unit operation for the study of carbon dioxide separation from methane. The hollow fibermembrane model was validated experimentally. The study of a double stage membranemodule with a permeate recycle, which was proposed to be the optimal configuration in previousstudies, was extended to consider the effects of the module characteristics (such as the fiber length,radius of the fiber bundle, diameter of the fibers, and porosity) on the process performance andeconomics. The gas processing cost (GPC) increased with increasing fiber length and bundle radius, anddecreased with increasing outer diameter of the fibers and porosity. At the same time, the separationefficiency (product quality) was also dependent on these module parameters. Therefore, the tradeoff forthe hollow fiber membrane module characteristics needs to be determined based on the minimum GPCwith respect to the desired product purity.

0199 Using machine learning to efficiently use multiple experts to assign occupational lead exposure estimates in a case-control study

Friesen, Melissa C,Locke, Sarah J,Zaebst, Dennis,Viet, Susan,Shortreed, Susan,Chen, Yu-Cheng,Koh, Dong-Hee,Pardo, Larissa,Schwartz, Kendra L,Davis, Faith G,Stewart, Patricia A,Colt, Joanne S,Purdue, M BMJ Publishing Group Ltd 2014 Occupational and environmental medicine Vol.71 No.suppl1

<P><B>Objectives</B></P><P>We applied machine learning approaches to efficiently assist multiple experts to transparently estimate occupational lead exposure in a case-control study of renal cell carcinoma.</P><P><B>Method</B></P><P>We used hierarchical cluster models to classify the 7154 study jobs with occupational history and job/industry questionnaires into 360 groups with similar responses. Each group was reviewed independently by two or three experts and was assigned probabilities of lead exposure (<5%, ≥5– <50%, ≥50%) for three time periods (<1980, 1980–1994, ≥1995). When the group’s mean response pattern suggested within-group exposure variability, experts identified programmable conditions that defined the rating differences where possible or flagged the group for further review. After splitting jobs that overlapped time periods at the calendar cut point, the 9992 job/time periods were assigned their relevant expert/group/time period estimate. Classification and regression tree (CART) models were developed to predict each expert’s expected assignment, based on previous decisions, to assign estimates for jobs in groups that expert had not assessed and for jobs requiring further review.</P><P><B>Results</B></P><P>In preliminary analyses, CART models predicted 91–96% of the experts’ pre-1995 estimates and 77–96% of ≥1995 estimates. CART estimates were assigned to 3–48% of the job/time periods, varying by expert. Overall, 92% of the job/time periods were assigned the same estimate by at least two experts.</P><P><B>Conclusions</B></P><P>Our framework reduced the number of exposure decisions needed from each expert compared to job-by-job assessment. Future work will use CART models to identify differences between experts to be resolved and incorporate frequency and intensity of lead exposure estimates.</P>

Hollow fiber membrane model for gas separation: Process simulation, experimental validation and module characteristics study

Ahmad, Faizan,Lau, K.K.,Lock, S.S.M.,Rafiq, Sikander,Khan, Asad Ullah,Lee, Moonyong Elsevier 2015 Journal of industrial and engineering chemistry Vol.21 No.-

<P><B>Abstract</B></P> <P>Conceptual process simulations and optimization are essential in the design, operation and troubleshooting stages of a membrane-based gas separation system. Despite this, there are few mathematical models/tools associated with a hollow fiber membrane module available in a commercial process simulator. A mathematical model dealing with the hollow fiber module characteristics that can be included within a commercial process simulator is needed to examine the performance and economics of a gas separation system. In this study, a hollow fiber membrane model was incorporated in Aspen HYSYS as a user defined unit operation for the study of carbon dioxide separation from methane. The hollow fiber membrane model was validated experimentally. The study of a double stage membrane module with a permeate recycle, which was proposed to be the optimal configuration in previous studies, was extended to consider the effects of the module characteristics (such as the fiber length, radius of the fiber bundle, diameter of the fibers, and porosity) on the process performance and economics. The gas processing cost (GPC) increased with increasing fiber length and bundle radius, and decreased with increasing outer diameter of the fibers and porosity. At the same time, the separation efficiency (product quality) was also dependent on these module parameters. Therefore, the tradeoff for the hollow fiber membrane module characteristics needs to be determined based on the minimum GPC with respect to the desired product purity.</P>

Electronic and optical properties of strain-locked metallic Ti2O3 films

Lahneman D.J.,Kim H.,Jiang H.,Mathews S.A.,Lock E.,Prestigiacomo J.,Qazilbash M.M.,Rohde C.,Piqué A. 한국물리학회 2023 Current Applied Physics Vol.47 No.-

We successfully grow corundum structured Ti2O3 films on c-plane sapphire substrates using pulsed laser deposition. Temperature dependent resistivity measurements show that a metal to insulator transition (MIT) is suppressed, showing conducting behavior at all temperatures. Samples still show an increase in resistivity as temperature is decreased, a characteristic indicative of a semiconducting phase. Our films exhibit grain size on the order of 30 nm which induce a strain consistent with nanoparticle Ti2O3 showing a (c/a) ratio of 2.7. The imposed strain causes an increase in the c-axis length as the temperature is decreased, and thereby suppresses the transition to an insulating phase. Our optical data agrees with this result, showing the lack of a band gap and the electronic structure consistent with bulk high temperature metallic Ti2O3 with the a1g - eπg interband transition shifted down to 0.7 eV from its bulk insulating value of ~1 eV.